TY - JOUR A1 - Becher, Stefan A1 - Gerl, Armin ED - Sarne, Giuseppe Maria Luigi ED - Ma, Jianhua ED - Rosaci, Domenico ED - Srivastava, Gautam T1 - ConTra Preference Language: Privacy Preference Unification via Privacy Interfaces JF - Sensors N2 - After the enactment of the GDPR in 2018, many companies were forced to rethink their privacy management in order to comply with the new legal framework. These changes mostly affect the Controller to achieve GDPR-compliant privacy policies and management.However, measures to give users a better understanding of privacy, which is essential to generate legitimate interest in the Controller, are often skipped. We recommend addressing this issue by the usage of privacy preference languages, whereas users define rules regarding their preferences for privacy handling. In the literature, preference languages only work with their corresponding privacy language, which limits their applicability. In this paper, we propose the ConTra preference language, which we envision to support users during privacy policy negotiation while meeting current technical and legal requirements. Therefore, ConTra preferences are defined showing its expressiveness, extensibility, and applicability in resource-limited IoT scenarios. In addition, we introduce a generic approach which provides privacy language compatibility for unified preference matching. KW - privacy KW - preference language KW - legal factors KW - GDPR KW - usability Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-11218 SN - 1424-8220 VL - 22 IS - 14 PB - MDPI CY - Basel, Switzerland ER - TY - THES A1 - Lachat, Paul T1 - Detecting Inference Attacks Involving Sensor Data N2 - The collection of personal information by organizations has become increasingly essential for social interactions. Nevertheless, according to the GDPR (General Data Protection Regulation), the organizations have to protect collected data. Access Control (AC) mechanisms are traditionally used to secure information systems against unauthorized access to sensitive data. The increased availability of personal sensor data, thanks to IoT-oriented applications, motivates new services to offer insights about individuals. Consequently, data mining algorithms have been proposed to infer personal insights from collected sensor data. Although they can be used for genuine purposes, attackers can leverage those outcomes, combining them with other type of data, and further breaching individuals’ privacy. Thus, bypassing AC mechanisms thanks to such insights is a concrete problem. We propose an inference detection system based on the analysis of queries issued on a sensor database. The knowledge obtained through these queries, and the inference channels corresponding to the use of data mining algorithms on sensor data to infer individual information, are described using Raw sensor data based Inference ChannEl Model (RICE-M). The detection is carried out by RICE-M based inference detection System (RICE-Sy). RICE-Sy considers at the time of the query, the knowledge that a user obtains via a new query and has obtained via his query history, and determines whether this is sufficient to allow that user to operate a channel. Thus, privacy protection systems can take advantage of the inferences detected by RICE-Sy, taking into account individuals’ information obtained by the attackers via a database of sensors, to further protect these individuals. Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-14149 ER - TY - THES A1 - Schlenker, Florian T1 - Delaunay Configuration B-Splines N2 - The generalization of univariate splines to higher dimensions is not straightforward. There are different approaches, each with its own advantages and drawbacks. A promising approach using Delaunay configurations and simplex splines is due to Neamtu. After recalling fundamentals of univariate splines, simplex splines, and the wellknown, multivariate DMS-splines, we address Neamtu’s DCB-splines. He defined two variants that we refer to as the nonpooled and the pooled approach, respectively. Regarding these spline spaces, we contribute the following results. We prove that, under suitable assumptions on the knot set, both variants exhibit the local finiteness property, i.e., these spline spaces are locally finite-dimensional and at each point only a finite number of basis candidate functions have a nonzero value. Additionally, we establish a criterion guaranteeing these properties within a compact region under mitigated assumptions. Moreover, we show that the knot insertion process known from univariate splines does not work for DCB-splines and reason why this behavior is inherent to these spline spaces. Furthermore, we provide a necessary criterion for the knot insertion property to hold true for a specific inserted knot. This criterion is also sufficient for bivariate, nonpooled DCB-splines of degrees zero and one. Numerical experiments suggest that the sufficiency also holds true for arbitrary spline degrees. Univariate functions can be approximated in terms of splines using the Schoenberg operator, where the approximation error decreases quadratically as the maximum distance between consecutive knots is reduced. We show that the Schoenberg operator can be defined analogously for both variants of DCB-splines with a similar error bound. Additionally, we provide a counterexample showing that the basis candidate functions of nonpooled DCB-splines are not necessarily linearly independent, contrary to earlier statements in the literature. In particular, this implies that the corresponding functions are not a basis for the space of nonpooled DCB-splines. N2 - Univariate Splines können nicht unmittelbar auf mehrere Dimensionen verallgemeinert werden. Jedoch gibt es verschiedene Ansätze mit jeweils unterschiedlichen Vor- und Nachteilen. Eine vielversprechende Herangehensweise, die Delaunay-Konfigurationen und Simplex-Splines verwendet, stammt von Neamtu. Nachdem wir die Grundlagen von univariaten Splines, Simplex-Splines und den bekannten multivariaten DMS-Splines wiederholt haben, beschäftigen wir uns mit Neamtus DCB-Splines. Er führte zwei verschiedene Varianten ein, die als nichtaggregierter beziehungsweise aggregierter Ansatz bezeichnet werden. In Bezug auf diese Splineräume präsentieren wir die folgenden Ergebnisse. Wir zeigen zum einen, dass beide Varianten unter geeigneten Voraussetzungen an die Knotenmenge die sogenannte Lokale-Endlichkeits-Eigenschaft besitzen. Dies bedeutet, dass die Splineräume lokal endlichdimensional sind und dass an jedem Punkt nur eine endliche Anzahl der Kandidaten an Basisfunktionen einen von null verschiedenen Wert aufweist. Zusätzlich ermitteln wir ein Kriterium, welches diese Eigenschaften auf einem kompakten Gebiet auch unter schwächeren Voraussetzungen garantiert. Darüber hinaus zeigen wir, dass der von den univariaten Splines her bekannte Prozess des Knoteneinfügens für DCB-Splines nicht funktioniert, und begründen, warum dieses Verhalten in der Natur dieser Splineräume liegt. Außerdem geben wir ein notwendiges Kriterium dafür an, dass die Knoteneinfüge-Eigenschaft für einen bestimmten einzufügenden Knoten gegeben sein kann. Für bivariate nicht-aggregierte DCB-Splines von Grad null und eins ist dieses Kriterium auch hinreichend. Numerische Experimente legen ferner die Vermutung nahe, dass dies unabhängig vom Splinegrad der Fall ist. Univariate Funktionen können mithilfe des Schoenberg-Operators durch Splines approximiert werden. Dabei hat eine Verringerung des maximalen Abstands zweier aufeinanderfolgender Knoten eine quadratische Verringerung des Approximationsfehlers zur Folge. Wir zeigen, dass der Schoenberg-Operator für beide Variaten von DCB-Splines auf analoge Art und Weise und mit einer ähnlichen Fehlerschranke definiert werden kann. Zusätzlich geben wir ein Gegenbeispiel an, das zeigt, dass die Basisfunktions-Kandidaten der nicht-aggregierten DCB-Splines nicht notwendigerweise linear unabhängig sind, was einen Gegensatz zu früheren Behauptungen in der Literatur darstellt. Dies impliziert insbesondere, dass die entsprechenden Funktionen keine Basis für den Raum der nicht-aggregierten DCB-Splines bilden. KW - Multivariate splines KW - Simplex splines KW - Delaunay triangulations KW - Delaunay configurations KW - Neamtu, Marian KW - Spline KW - Bivariater Spline KW - Spline-Raum KW - Simplexspline KW - Neamtu, Marian Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-11225 ER - TY - THES A1 - Stier, Julian T1 - Structure of Artificial Neural Networks : Empirical Investigations N2 - Within one decade, Deep Learning overtook the dominating solution methods of countless problems of artificial intelligence. "Deep" refers to the deep architectures with operations in manifolds of which there are no immediate observations. For these deep architectures some kind of structure is pre-defined -- but what is this structure? With a formal definition for structures of neural networks, neural architecture search problems and solution methods can be formulated under a common framework. Both practical and theoretical questions arise from closing the gap between applied neural architecture search and learning theory. Does structure make a difference or can it be chosen arbitrarily? This work is concerned with deep structures of artificial neural networks and examines automatic construction methods under empirical principles to shed light on to the so called ``black-box models''. Our contributions include a formulation of graph-induced neural networks that is used to pose optimisation problems for neural architecture. We analyse structural properties for different neural network objectives such as correctness, robustness or energy consumption and discuss how structure affects them. Selected automation methods for neural architecture optimisation problems are discussed and empirically analysed. With the insights gained from formalising graph-induced neural networks, analysing structural properties and comparing the applicability of neural architecture search methods qualitatively and quantitatively we advance these methods in two ways. First, new predictive models are presented for replacing computationally expensive evaluation schemes, and second, new generative models for informed sampling during neural architecture search are analysed and discussed. KW - neural architecture KW - deep learning KW - graph induced neural networks Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-14968 ER - TY - THES A1 - Juhos, Michael T1 - Probabilistic and geometric aspects of classical and non-commutative lp-type spaces in high dimensions N2 - This cumulative dissertation contains selected contributions to the field of asymptotic geometric analysis and high-dimensional probability. It is divided into two chapters: Chapter 1 explains some of the necessary theoretical background. In Section 1.1 it first gives a very concise history of asymptotic geometric analysis in general and then of the objects under study in particular, setting out some cornerstones in the discovery of the functional-analytic, geometric, and probabilistic properties of the spaces under consideration. The next section (1.2) gives the precise definitions and very basic properties of the three lp-type spaces that play a role in the contributed articles: the classical lp-sequence spaces, the mixed-norm sequence spaces, and the Schatten-classes Sp, each in its infinite- and finite-dimensional version. Section 1.3 is dedicated to the interplay between geometry and probability, expounding the general idea, introducing a few of the common tools, and exemplifying these on two kinds of limit theorems: Schechtman-Schmuckenschläger-type results and Poincaré-Maxwell-Borel lemmas. The first chapter concludes with Section 1.4, addressing a small sample of open questions pertaining to the contributed articles which are not answered in said articles and may be the interest of future research. The entirety of Chapter 2 consists of the contributed articles. N2 - Diese kumulative Dissertation enthält ausgewählte Beiträge zum Gebiet der asymptotischen geometrischen Analyse und der hochdimensionalen Wahrscheinlichkeit. Sie ist in zwei Kapitel geteilt: Kapitel 1 erklärt ein wenig des notwendigen theoretischen Hintergrunds. Abschnitt 1.1 bringt eine sehr kurz gefasste Geschichte der asymptotischen geometrischen Analyse im Allgemeinen und der Studienobjekte im Speziellen und legt einige Eckpunkte der Entdeckung der funktionalanalytischen, geometrischen und probabilistischen Eigenschaften der betrachteten Räume dar. Der nächste Abschnitt (1.2) gibt die genauen Definitionen und sehr grundlegenden Eigenschaften jener drei lp-artigen Räume, die in den beigetragenen Artikeln eine Rolle spielen: die klassischen lp-Folgenräume, die Folgenräume mit gemischter Norm und die Schattenklassen Sp, jeweils in der unendlich- und der endlichdimensionalen Version. Abschnitt 1.3 ist dem Zusammenspiel von Geometrie und Wahrscheinlichkeit gewidmet, er erörtert die allgemeine Idee, stellt einige der gebräuchlichen Werkzeuge vor und gibt zwei Beispiele von Grenzwertsätzen dazu: Schechtman-Schmuckenschläger-artige Ergebnisse und Poincaré-Maxwell-Borel-Lemmas. Das erste Kapitel schließt mit Abschnitt 1.4, der einen kleinen Satz von offenen Fragen anspricht, die zu den beigetragenen Artikeln gehören, darin aber nicht beantwortet werden und die das Interesse künftiger Forschung sein mögen. Kapitel 2 besteht zur Gänze aus den beigetragenen Artikeln. KW - functional analysis KW - asymptotic geometric analysis KW - limit theorems KW - lp-space KW - Schatten class Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-14857 ER - TY - THES A1 - Auer, Michael T1 - Improving Automated Android Test Generation N2 - Mobile apps are nowadays the preferred means to accomplish ubiquitous tasks like messaging, e-commerce and even playing games. Often, there exist multiple apps for the same purpose, and it is the choice of the end user to pick an appropriate app. Apps that behave unexpected, e.g., crash frequently, are sooner or later replaced, which isundesirable for the companies developing such apps. Thus, it is essential to tests apps properly before they are released onto the market. However, testing manually is often not only too cost-intensive but also too time-consuming in the short development phase, thus an automated solution is preferred. Testing mobile apps automatically received increased attention in the last decade from primarily people in academia, and several testing techniques evolved. One technique that yielded promising results, especially in different domains, is search-based software testing in which a metaheuristic, e.g., a genetic algorithm, is applied to solve an optimisation problem, e.g., test generation. A main objective of test generation is to produce tests that reveal as many faults as possible. This in turn requires the generation of tests that deeply explore the tested app. The core metric to quantify how much code tests cover is the measurement of code coverage, which can be computed at different levels of granularity ranging from determining the fraction of covered activities to a very fine-grained measurement that calculates the percentage of covered lines. This coverage information is then often used to guide the search of the employed metaheuristic. However, current automated test generation approaches produce tests with a rather low code coverage. Thus, a substantial part of tested apps remains unexplored, which in turn misses revealing deeply residing faults. We identified three core issues that are directly related to the generation of low-coverage tests. First, the applicability of current test generators is often limited. This comprises the fact that current state-of-the-art code coverage tools are incapable of instrumenting a substantial number of apps and consequently, test generators cannot utilise detailed coverage information during exploration. In addition, test generators are often only equipped with a primitive set of actions that are insufficient to simulate system events and complex user inputs. Second, the test execution is extremely time-consuming. This includes among other things the overhead associated with executing individual actions, intermediate restart operations as well as fitness evaluations. Since search-based algorithms require a substantial number of test executions to play out their strengths, the slow test execution impedes the effectiveness of the search. Third, the guidance offered by search-based algorithms is often hampered by applying inadequate fitness functions or by using non-representation-specific variation operators. In this thesis we address the problem of low-coverage tests in the Android domain by proposing several enhancements for the three identified core issues. Concerning the applicability problem, we provide the implementation of a robust code coverage tool that is capable of measuring coverage at different levels of granularity and requires no access to the source code. We also propose to include actions that can simulate system events as well as complex user inputs. Regarding the performance issue, we suggest the integration of a surrogate model that is capable of predicting the outcome of individual actions or complete tests over time in order to reduce the overall test execution costs. With respect to the lack of guidance offered by traditional search-based algorithms, we suggest alternative search strategies. In the case of a deceptive fitness landscape, we propose using novelty search algorithms. Alternatively, we suggest utilising estimation of distribution algorithms that require no crossover or mutation perators to sample new tests. While all those enhancements had a positive impact on the Android test generation process, the individual empirical studies highlighted that further research is necessary to unleash the full power of the proposed search-based algorithms. In particular, exploring complex user interfaces meaningfully requires more attention whether by introducing additional actions or by extracting valuable hints to infer reasonable text inputs. In addition, the guidance offered by fitness functions is often limited because they are either designed too coarse at all or do not accurately reflect the search objectives. Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-14955 ER - TY - JOUR A1 - Lengler, Johannes A1 - Opris, Andre A1 - Sudholt, Dirk T1 - Analysing Equilibrium States for Population Diversity JF - Algorithmica (ISSN: 1432-0541) N2 - Population diversity is crucial in evolutionary algorithms as it helps with global exploration and facilitates the use of crossover. Despite many runtime analyses showing advantages of population diversity, we have no clear picture of how diversity evolves over time. We study how the population diversity of (μ+1)algorithms, measured by the sum of pairwise Hamming distances, evolves in a fitness-neutral environment. We give an exact formula for the drift of population diversity and show that it is driven towards an equilibrium state. Moreover, we bound the expected time for getting close to the equilibrium state. We find that these dynamics, including the location of the equilibrium, are unaffected by surprisingly many algorithmic choices. All unbiased mutation operators with the same expected number of bit flips have the same effect on the expected diversity. Many crossover operators have no effect at all, including all binary unbiased, respectful operators. We review crossover operators from the literature and identify crossovers that are neutral towards the evolution of diversity and crossovers that are not. KW - Evolutionary algorithms KW - Runtime analysis KW - Diversity KW - Population dynamics Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2406282100292.409184699704 SN - 0178-4617 SN - 1432-0541 VL - 86 IS - 7 SP - 2317 EP - 2351 PB - Springer US CY - New York ER - TY - JOUR A1 - Schulte, Lukas A1 - Ledel, Benjamin A1 - Herbold, Steffen T1 - Studying the explanations for the automated prediction of bug and non-bug issues using LIME and SHAP JF - Empirical Software Engineering (ISSN: 1573-7616) N2 - Context The identification of bugs within issues reported to an issue tracking system is crucial for triage. Machine learning models have shown promising results for this task. However, we have only limited knowledge of how such models identify bugs. Explainable AI methods like LIME and SHAP can be used to increase this knowledge. Objective We want to understand if explainable AI provides explanations that are reasonable to us as humans and align with our assumptions about the model’s decision-making. We also want to know if the quality of predictions is correlated with the quality of explanations. Methods We conduct a study where we rate LIME and SHAP explanations based on their quality of explaining the outcome of an issue type prediction model. For this, we rate the quality of the explanations, i.e., if they align with our expectations and help us understand the underlying machine learning model. Results We found that both LIME and SHAP give reasonable explanations and that correct predictions are well explained. Further, we found that SHAP outperforms LIME due to a lower ambiguity and a higher contextuality that can be attributed to the ability of the deep SHAP variant to capture sentence fragments. Conclusion We conclude that the model finds explainable signals for both bugs and non-bugs. Also, we recommend that research dealing with the quality of explanations for classification tasks reports and investigates rater agreement, since the rating of explanations is highly subjective. KW - Explainable AI KW - LIME KW - SHAP KW - Issue type prediction Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2409232103207.812648424894 SN - 1382-3256 SN - 1573-7616 VL - 29 IS - 4 PB - Springer US CY - New York ER - TY - JOUR A1 - Aistleitner, Christoph A1 - Frühwirth, Lorenz A1 - Prochno, Joscha T1 - Diophantine conditions in the law of the iterated logarithm for lacunary systems JF - Probability Theory and Related Fields (ISSN: 1432-2064) N2 - It is a classical observation that lacunary function systems exhibit many properties which are typical for systems of independent random variables. However, it had already been observed by Erdős and Fortet in the 1950s that probability theory’s limit theorems may fail for lacunary sums (sum f(n_k x)) if the sequence ((n_k)_{k ge 1}) has a strong arithmetic “structure”. The presence of such structure can be assessed in terms of the number of solutions k, l of two-term linear Diophantine equations (an_k - bn_l = c). As the first author proved with Berkes in 2010, saving an (arbitrarily small) unbounded factor for the number of solutions of such equations compared to the trivial upper bound, rules out pathological situations as in the Erdős–Fortet example, and guarantees that (sum f(n_k x)) satisfies the central limit theorem (CLT) in a form which is in accordance with true independence. In contrast, as shown by the first author, for the law of the iterated logarithm (LIL) the Diophantine condition which suffices to ensure “truly independent” behavior requires saving this factor of logarithmic order. In the present paper we show that, rather surprisingly, saving such a logarithmic factor is actually the optimal condition in the LIL case. This result reveals the remarkable fact that the arithmetic condition required of ((n_k)_{k ge 1}) to ensure that (sum f(n_k x)) shows “truly random” behavior is a different one at the level of the CLT than it is at the level of the LIL: the LIL requires a stronger arithmetic condition than the CLT does. KW - Lacunary trigonometric sums KW - Law of the iterated logarithm KW - Diophantine equations Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2406190937284.886045166092 SN - 0178-8051 SN - 1432-2064 VL - 192 IS - 1 SP - 545 EP - 574 PB - Springer CY - Berlin/Heidelberg ER - TY - JOUR A1 - Beurskens, Michael A1 - Scherzinger, Stefanie T1 - Legal Perspectives on Research Data Storage JF - Datenbank-Spektrum (ISSN: 1618-2162) N2 - Responsibly managing research data has become increasingly important for researchers, especially within the database research community. Despite significant progress in best practices, the state-of-the-art in research data storage is lacking from a legal perspective. We introduce the stakeholders and the dynamic nature of their relationships (such as researchers changing affiliation) and observe that no existing infrastructure for research data storage fully meets their requirements. Therefore, we emphasize the need to design a comprehensive system architecture for research data storage that is aligned with legal considerations from the start, rather than as an afterthought. KW - Storage Contract KW - Copyright KW - Sui Generis Right KW - Privacy KW - Trade Secrets KW - Research Data Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2410012125227.647518861484 SN - 1618-2162 SN - 1610-1995 VL - 24 IS - 2 SP - 85 EP - 95 PB - Springer CY - Berlin/Heidelberg ER - TY - JOUR A1 - Franke, Jan A1 - Heinrich, Florian A1 - Reisch, Raven T. T1 - Vision based process monitoring in wire arc additive manufacturing (WAAM) JF - Journal of Intelligent Manufacturing (ISSN: 1572-8145) N2 - A stable welding process is crucial to obtain high quality parts in wire arc additive manufacturing. The complexity of the process makes it inherently unstable, which can cause various defects, resulting in poor geometric accuracy and material properties. This demands for in-process monitoring and control mechanisms to industrialize the technology. In this work, process monitoring algorithms based on welding camera image analysis are presented. A neural network for semantic segmentation of the welding wire is used to monitor the working distance as well as the horizontal position of the wire during welding and classic image processing techniques are applied to capture spatter formation. Using these algorithms, the process stability is evaluated in real time and the analysis results enable the direction independent closed-loop-control of the manufacturing process. This significantly improves geometric fidelity as well as mechanical properties of the fabricated part and allows the automated production of parts with complex deposition paths including weld bead crossings, curvatures and overhang structures. KW - Wire arc additive manufacturing KW - Vision based monitoring KW - Machine learning KW - Nozzle-to-work distance monitoring KW - Contact tube wear off detection KW - Spatter detection Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2405052141549.085870766506 SN - 0956-5515 SN - 1572-8145 VL - 36 IS - 3 SP - 1711 EP - 1721 PB - Springer US CY - New York ER - TY - JOUR A1 - Andraschko, Bernhard A1 - Danner, Julian A1 - Kreuzer, Martin T1 - SAT Solving Using XOR-OR-AND Normal Forms JF - Mathematics in Computer Science (ISSN: 1661-8289) N2 - This paper introduces the XOR-OR-AND normal form (XNF) for logical formulas. It is a generalization of the well-known Conjunctive Normal Form (CNF) where literals are replaced by XORs of literals. As a first theoretic result, we show that every CNF formula is equisatisfiable to a formula in 2-XNF, i.e., a formula in XNF where each clause involves at most two XORs of literals. Subsequently, we present an algorithm which converts Boolean polynomials efficiently from their Algebraic Normal Form (ANF) to formulas in 2-XNF. Experiments with the cipher ASCON-128 show that cryptographic problems, which by design are based strongly on XOR-operations, can be represented using far fewer variables and clauses in 2-XNF than in CNF. In order to take advantage of this compact representation, new SAT solvers based on input formulas in 2-XNF need to be designed. By taking inspiration from graph-based 2-CNF SAT solving, we devise a new DPLL-based SAT solver for formulas in 2-XNF. Among others, we present advanced pre- and in-processing techniques. Finally, we give timings for random 2-XNF instances and instances related to key recovery attacks on round reduced ASCON-128, where our solver outperforms state-of-the-art alternative solving approaches. KW - - KW - SAT solving KW - XOR constraint KW - Algebraic normal form KW - Implication graph KW - Cryptographic attack KW - 03B70 KW - 13P15 KW - 05C90 KW - 94A60 Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2502242130589.859216082138 SN - 1661-8270 SN - 1661-8289 VL - 18 IS - 4 PB - Springer International Publishing CY - Cham ER - TY - JOUR A1 - Kosch, Harald A1 - Brunie, Lionel A1 - Mayer, Tobias A1 - Hasan, Omar A1 - Schiedermeier, Maximilian T1 - Anonymous voting using distributed ledger-assisted secure multi-party computation JF - Applied Network Science N2 - High voter turnout in elections and referendums is desirable to ensure a robust democracy. Secure electronic voting is a vision for the future of elections and referendums. Such a system can counteract factors hindering strong voter turnout such as the requirement of physical presence during limited hours at polling stations. However, this vision brings transparency and confidentiality requirements that render the design of such solutions challenging. Specifically, the counting implementation must support reproducibility, and the choice of individual voters must remain confidential. In this paper, we propose and evaluate a novel referendum protocol that ensures transparency, confidentiality, and integrity, in trustless networks. The protocol is built by combining secure multi-party computation and distributed ledger technology, e.g., a Blockchain. The persistence and immutability of the protocol communication allow verifiability of the referendum outcome by any participant. Voters therefore do not need to trust third parties. We provide a formal description and conduct a thorough security evaluation of our proposal. KW - E-voting KW - Distributed ledger KW - Trustless networks KW - Transparency Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15176 VL - 2024 IS - 9 PB - Springer International Publishing CY - Cham (Schweiz) ER - TY - JOUR A1 - Ghodselahi, Abdolhamid A1 - Kuhn, Fabian T1 - Toward Online Mobile Facility Location on General Metrics JF - Theory of Computing Systems N2 - We introduce an online variant of mobile facility location (MFL) (introduced by Demaine et al. (SODA 258–267 2007)). We call this new problem online mobile facility location (OMFL). In the OMFL problem, initially, we are given a set of k mobile facilities with their starting locations. One by one, requests are added. After each request arrives, one can make some changes to the facility locations before the subsequent request arrives. Each request is always assigned to the nearest facility. The cost of this assignment is the distance from the request to the facility. The objective is to minimize the total cost, which consists of the relocation cost of facilities and the distance cost of requests to their nearest facilities. We provide a lower bound for the OMFL problem that even holds on uniform metrics. A natural approach to solve the OMFL problem for general metric spaces is to utilize hierarchically well-separated trees (HSTs) and directly solve the OMFL problem on HSTs. In this paper, we provide the first step in this direction by solving a generalized variant of the OMFL problem on uniform metrics that we call G-OMFL. We devise a simple deterministic online algorithm and provide a tight analysis for the algorithm. The second step remains an open question. Inspired by the k-server problem, we introduce a new variant of the OMFL problem that focuses solely on minimizing movement cost. We refer to this variant as M-OMFL. Additionally, we provide a lower bound for M-OMFL that is applicable even on uniform metrics. KW - Mobile resources KW - Online requests KW - Competitive analysis KW - General cost function KW - Movement minimization Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2024022609363705445898 VL - 67 IS - 6 SP - 1268 EP - 1306 PB - Springer Nature CY - Berlin ER - TY - JOUR A1 - von der Heyde, Markus A1 - Gerl, Armin T1 - Entwicklungsstand der CIO-Funktion und hochschulübergreifenden IT-Governance im Kontext der Digitalen Transformation an Hochschulen in Bayern JF - HMD Praxis der Wirtschaftsinformatik N2 - Die Hochschulen befinden sich durch vielfältige Veränderungs-prozesse in Verbindung mit dem Einsatz von Informationstechnologien (IT) aufdem Weg der Digitalen Transformation. Diese Digitale Transformation der Hoch-schulen umfasst intensive Veränderungsprozesse in der gesamten Hochschulkulturin Lehre, Forschung und Verwaltung in übergreifender und strukturierter Weise.Seit vielen Jahren werden vielfältige Digitalisierungsvorhaben zur Modernisierungvon einzelnen Prozessen an den Hochschulen umgesetzt. Die Leitungen der Re-chenzentren leisten mit der Umsetzung von IT-Projekten einen zentralen Beitrag zudiesem Wandel. Mit der Einführung der CIO-Funktion in den Hochschulleitungenund der hochschulübergreifenden Kooperationen hat sich die IT-Governance wei-terentwickelt. Insbesondere für die Digitale Transformation werden Strukturen zurKoordination der übergreifenden Vorhaben benötigt, wobei zusätzlich zur IT-Lei-tung eine Vielzahl von Funktionsträgern mit fachlichen Aufgaben aus Forschung,Lehre und Verwaltung involviert ist. Es stellt sich die Frage, wie die Digitale Trans-formation an Hochschulen gesteuert werden kann und in welcher organisatorischenForm sich die Aufgaben und Verantwortlichkeiten im Hochschulkontext realisierenlassen. An der Weiterentwicklung der IT-Governance an bayerischen Hochschulenwird beispielhaft erläutert, welche übergreifenden Aufgaben der Koordination vonBedarf und Versorgung mit IT-Services zwischen und innerhalb der Hochschulenbestehen. Die CIO-Funktion wird durch die Verankerung in der Leitungsebene derFunktion des Chief Digital Officers (CDO) aus der Wirtschaft ähnlicher, auch wennin Hochschulen aufgrund der klassischen Ressort-Einteilung die Rolle oft als Vize-präsident:in für Digitalisierung bezeichnet wird. KW - Digitale Transformation KW - IT-Governance KW - Hochschulen KW - Bildung KW - CIO KW - CDO Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2022072222053919381076 VL - 2022 IS - 59 SP - 881 EP - 895 PB - Springer Nature CY - Berlin ER - TY - JOUR A1 - Hevia Fajardo, Mario Alejandro A1 - Sudholt, Dirk T1 - Self-adjusting Population Sizes for Non-elitist Evolutionary Algorithms: why Success Rates Matter JF - Algorithmica N2 - Evolutionary algorithms (EAs) are general-purpose optimisers that come with several parameters like the sizes of parent and offspring populations or the mutation rate. It is well known that the performance of EAs may depend drastically on these parameters. Recent theoretical studies have shown that self-adjusting parameter control mechanisms that tune parameters during the algorithm run can provably outperform the best static parameters in EAs on discrete problems. However, the majority of these studies concerned elitist EAs and we do not have a clear answer on whether the same mechanisms can be applied for non-elitist EAs. We study one of the best-known parameter control mechanisms, the one-fifth success rule, to control the offspring population size λ in the non-elitist (1, λ) EA. It is known that the (1, λ) EA has a sharp threshold with respect to the choice of λ where the expected runtime on the benchmark function OneMax changes from polynomial to exponential time. Hence, it is not clear whether parameter control mechanisms are able to find and maintain suitable values of λ. For OneMax we show that the answer crucially depends on the success rates (i. e. a one-(s + 1)-th success rule). We prove that, if the success rate is appropriately small, the self-adjusting (1, λ) EA optimises OneMax in O(n) expected generations and O(n log n) expected evaluations, the best possible runtime for any unary unbiased black-box algorithm. A small success rate is crucial: we also show that if the success rate is too large, the algorithm has an exponential runtime on OneMax and other functions with similar characteristics. KW - Evolutionary algorithms KW - Parameter control KW - Theory KW - Runtime analysis KW - Non-elitism Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2023102616463077837436 VL - 86 IS - 2 SP - 526 EP - 565 PB - Springer Nature CY - Berlin ER - TY - JOUR A1 - Gagin, Stepan A1 - Bettermann, Michael A1 - de Meer, Hermann T1 - Multi-vector optimization scheme for distributed components in energy islands JF - e+i Elektrotechnik und Informationstechnik N2 - Recent advancements in energy systems, such as the emergence of prosumers and sector coupling approaches, introduce additional flexibilities over multiple energy sectors, such as heating, electricity, and mobility. Due to the complexity of such distributed systems, the optimization of energy allocation is a non-trivial task, especially considering constraints and limitations introduced by distributed devices or sub-systems. Additionally, the variety of devices forces approaches to be highly situational and not universally applicable. In this paper, a two-level optimization scheme is proposed, which aims at reducing the optimization complexity of sector-coupled systems. The multi-vector optimization embedded in the two-level optimization scheme is formulated as a mixed-integer linear problem, optimizing the energy flow between domains, which are modeled as an abstraction of a sector. Distributed devices are modeled as components that represent an abstraction of devices connected to an energy domain. The optimization process is evaluated based on the data from a residential complex in Ghent, Belgium. It shows that the approach is capable of minimizing costs, CO2 emissions, and dependency on external resources. KW - Energy optimization KW - Multi-energy systems KW - Sector coupling KW - Energy Management KW - Systems Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2023110413071966670578 VL - 140 IS - 5 SP - 460 EP - 470 PB - Springer Nature CY - Berlin ER - TY - JOUR A1 - Fink, Thomas A1 - Forster, Brigitte A1 - Heinrich, Florian T1 - Gabor’s “complex signal” revisited: Complexifying frames and bases JF - PAMM (Proceedings in Applied Mathematics and Mechanics) N2 - In 1946, Dennis Gabor introduced the analytic signal 𝑓 + 𝑖𝐻𝑓 for real-valued signals 𝑓. Here, 𝐻 is the Hilbert transform. This complexification of functions allows for an analysis of their amplitude and phase information and has ever since given well-interpretable insight into the properties of the signals over time. The idea of complexification has been reconsidered with regard to many aspects: examples are the dual tree complex wavelet transform, or via the Riesz transform and the monogenic signal, that is, a multi-dimensional version of the Hilbert transform, which in combination with multi-resolution approaches leads to Riesz wavelets, and others. In this context, we ask two questions: - Which pairs of real orthonormal bases (ONBs), Riesz bases, frames and Parseval frames {𝑓 𝑛 } 𝑛∈ℕ and {𝑔 𝑛 } 𝑛∈ℕ can be “rebricked” to complex-valued ones {𝑓𝑛 + 𝑖𝑔 𝑛 } 𝑛∈ℕ? - And which real operators A allow for rebricking via the ansatz {𝑓𝑛 + 𝑖𝐴𝑓𝑛 } 𝑛∈ℕ? In this short note, we give answers to these questions with regard to a characterization which linear operators A are suitable for rebricking while maintaining the structure of the original real valued family. Surprisingly, the Hilbert transform is not among them. Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2023091815015485698899 VL - 23 IS - 3 PB - Wiley CY - Hoboken ER - TY - THES A1 - Stumpf, Peter Frederik T1 - Partial Representation Extension and Simultaneous Representation of Intersection Graphs N2 - Many real world problems can be modeled with geometric intersection graphs. A (geometric) intersection representation of a graph G=(V,E) is a family {R_v}_{v\in V} of geometric objects such that two geometric objects R_u, R_v intersect if and only if the corresponding vertices u, v are adjacent in G. The most prominent class of intersection graphs are interval graphs, which have representations consisting only of intervals on the real line. Interval graphs have applications in genetics, scheduling, archaeology and many more fields. The recognition problem asks the question whether a given graph belongs to a certain graph class. Two natural generalizations of the recognition problem are the partial representation extension problem and the simultaneous representation problem. In the partial representation extension problem one is given a graph G and a partial representation, i.e., a representation of a subgraph of G. The question then is whether the partial representation can be extended to the whole graph G without changing the given partial representation. In the simultaneous representation problem one is given multiple graphs G_1,...,G_k that can have shared parts, and the question is whether there are representations of all input graphs such that shared vertices are represented by the same geometric objects. Often the sunflower case is considered, where the shared part of any two input graphs is the same. We determine the complexity of the partial representation extension problem and the simultaneous representation problem, especially in the sunflower case for various intersection graph classes. We also improve the running time for various intersection graph classes. In particular, we show that the partial representation extension problem for circular-arc graphs is NP-complete and that the simultaneous representation problem for interval graphs can be solved in linear time in the sunflower case, answering open questions from 2014 and 2010. KW - partial representation KW - simultaneous representation KW - sunflower representation Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15201 ER - TY - THES A1 - Ghosh Dastidar, Kanishka T1 - Using Context for Credit Card Fraud Detection N2 - Online payment fraud is one of the biggest challenges accompanying the ubiquitous adoption of digital payment methods. The academic literature shows that providing data-driven models with additional context of a transaction results in significant improvements in fraud detection performance. However, the methods used to generate suitable context representations often rely on human expert knowledge, which is expensive and suffers from several limitations. In this thesis, we propose different methods to automate this process by learning these context representations end-to-end on the fraud detection objective. Each of these methods is evaluated on millions of real-world transactions from Worldline, our industrial partner. Central to this thesis is our proposal of the Neural Aggregate Generator (NAG), a neural network that learns context representations automatically. The architecture of the NAG is designed to resemble the structure of expert feature aggregates, while also addressing their limitations. Our evaluation of the NAG reveals that it outperforms both approaches that use expert aggregates and other end-to-end methods across several months of testing. A thorough evaluation shows that the NAG improves over other approaches on several key factors including model size and robustness to shorter sequences. We propose several extensions to the NAG with the dual motive of improved alignment with expert aggregates and improved expressiveness. Our evaluation of these extensions shows comparable performance to the NAG with ancillary benefits in terms of prospective interpretability and model size. We also introduce the novel paradigm of using \lq future' transactions as context. Our analysis of real-world data from Worldline shows that verification of transactions are often delayed by several days and that within this delay there are often several transactions booked on the card which can be used as additional context. We show that this future context improves the performance of sequence models. Moreover, we also show that a balance between past and future context yields the best results and that using future context allows the use of shorter sequences overall. Beyond context-based fraud detection, we also provide an initial proposal of generating synthetic credit card data using Generative Adversarial Networks (GANs), showing that a Wasserstein GAN can be used to generated synthetic data similar to a popular publicly available credit card fraud dataset. We also describe several possible directions for future work including the incorporation of a adapted self-attention mechanism to the NAG and the use of transformers for synthetic data generation. N2 - Betrug bei Online-Zahlungen ist eine der größten Herausforderungen bei der weitverbreiteten Einführung digitaler Zahlungsmethoden. Die akademische Literatur zeigt, dass die Bereitstellung von datengesteuerten Modellen mit zusätzlichem Transaktionskontext zu einer erheblichen Verbesserung der Betrugserkennungsleistung führt. Die Methoden zur Generierung geeigneter Kontextrepräsentationen beruhen jedoch häufig auf menschlichem Expertenwissen, was teuer ist und einige Einschränkungen mit sich bringt. In dieser Arbeit schlagen wir verschiedene Methoden vor, um diesen Prozess zu automatisieren, indem diese Kontextrepräsentationen end-to-end auf das Ziel der Betrugserkennung hin erlernt werden. Jede dieser Methoden wird anhand von Millionen echter Transaktionen von Worldline, unserem industriellen Partner, bewertet. Zentral in dieser Arbeit ist unser Vorschlag des Neural Aggregate Generator (NAG), ein neuronales Netzwerk, das Kontextrepräsentationen automatisch erlernt. Die Architektur des NAGs ist so konzipiert, dass sie der Struktur von Expertenaggregaten ähnelt und gleichzeitig deren Einschränkungen adressiert. Unsere Bewertung des NAGs zeigt, dass es sowohl Ansätze, die Expertenaggregate verwenden, als auch andere end-to-end Methoden in mehreren Monaten des Testens übertrifft. Eine tiefergehende Bewertung zeigt, dass das NAG in mehreren wichtigen Faktoren, einschließlich der Modellgröße und der Robustheit gegenüber kürzeren Sequenzen, bessere Ergebnisse erzielt als andere Ansätze. Wir schlagen mehrere Erweiterungen des NAGs vor, die das doppelte Ziel verfolgen, eine bessere Übereinstimmung mit Expertenaggregaten und eine verbesserte Ausdruckskraft zu erreichen. Unsere Bewertung dieser Erweiterungen zeigt eine vergleichbare Leistung zum NAG mit zusätzlichen Vorteilen hinsichtlich der zukünftigen Interpretierbarkeit und der Modellgröße. Wir führen auch das neuartige Paradigma der Nutzung zukünftiger Transaktionen als Kontext ein. Unsere Analyse der Daten von Worldline zeigt, dass die Verifizierung von Transaktionen oft um mehrere Tage verzögert ist und dass während dieser Verzögerung oft mehrere Transaktionen auf der Karte gebucht werden, die als zusätzlicher Kontext verwendet werden können. Wir zeigen, dass dieser „zukünftige“ Kontext die Leistung von Sequenzmodellen verbessert. Darüber hinaus zeigen wir, dass ein Gleichgewicht zwischen vergangenem und zukünftigem Kontext die besten Ergebnisse liefert und dass die Nutzung zukünftigen Kontexts insgesamt kürzere Sequenzen ermöglicht. Über die kontextbasierte Betrugserkennung hinaus geben wir auch einen ersten Vorschlag zur Generierung synthetischer Kreditkartendaten mittels Generative Adversarial Networks (GANs) und zeigen, dass ein durch einen Wasserstein-GAN generierter Datensatz geeignet ist, um darauf Erkennungsmodelle zu trainieren. Wir beschreiben auch mehrere mögliche Richtungen für zukünftige Arbeiten, einschließlich der Integration eines angepassten Self-Attention Mechanismus in das NAG und der Verwendung von Transformern zur Generierung synthetischer Daten. KW - Credit Card Fraud Detection KW - Deep Learning KW - Neural Networks Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15561 ER - TY - THES A1 - Soller, Sebastian T1 - Anomaly Detection and Forecasting Techniques and their Applications Scenarios, Challenges and Limits in Industrial Production Settings N2 - What needs to be done to get machine learning and artificial intelligence from the lab to the shop floor? This work and its affiliated publications focus on challenges and solutions to apply machine learning applications inside industrial setups and what steps are needed to improve those setups. In industrial setups it is easy to run into a "hen and egg" problem. To gather data, the information which data to gather is ideally given beforehand and these information are not available when studying new setups and machines. In this work setups and concepts are created to dynamically connect to a network and start gathering data from available endpoints inside a manufacturing setup. The data streams of these endpoints are further analyzed to give an initial analysis of the data and advise further processing. To further analyze these data streams with the current advances in the machine learning field and AI, plug and play solutions are presented by manufacturers and scientific research. Limits are determined for this plug and play capability and solutions are provided to further improve upon the base solutions. The capability to apply commonly applied methods was analyzed and initially provided non-sufficient results. In the sub-fields of anomaly detection, regression analysis, forecasting and classification the addition of context information, such as production specific information and time dependent analysis were used to improve the results. Context information, especially periodic information, were further conceptualized and integrated into the initial data analysis. Difficulties with correct labeling of ground truth due to differing biases of participants were encountered, and counter measurements were proposed. Results of the classification, regression, forecast and context information extraction were investigated for their influence on the human operator. A significant change could be measured in multiple cases, just by providing information about underlying problems and errors. The Aforementioned machine learning methods further improved the performance of machine and operator. KW - Anomalieerkennung KW - Künstliche Intelligenz KW - Maschinelles Learning KW - Plug-and-Play Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15659 ER - TY - THES A1 - Frühwirth, Lorenz T1 - The Asymptotic Behavior of Birkhoff- and Lacunary Sums N2 - This doctoral thesis consists of three independently published research articles on the asymptoic behaviour of Lacunary- and Birkhoff sums. The former are sums formed by periodic functions and exponentially growing sequences of natural numbers. The corresponding summands often exhibit behavior typical of independent and identically distributed random variables. The methods used are of an analytical and probabilistic nature. The Birkhoff sums considered in this work are generated by the Kronecker sequence and by discontinuous functions. The methods employed are from the field of metric number theory, specifically classical results from continued fraction theory are utilized. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15677 ER - TY - GEN A1 - Mexis, Nico A1 - Lill, Bjarne A1 - Doleh, Yousef A1 - Katzenbeisser, Stefan T1 - Supplementary Material for the Work "Exposing the Gaps: The State of Supply Chain Coverage in Current Security Standards" N2 - This document contains the supplementary material for our work "Exposing the Gaps: The State of Supply Chain Coverage in Current Security Standards", which should be consulted for further information and details. While this supplement has not been peer-reviewed, the above article has. The reviewers also had access to all the data presented in this document during the review phase. The article is available from 26 July 2025 as part of the "IFIP Advances in Information and Communication Technology", volume 742: 10.1007/978-3-031-94924-1_14 KW - Supply Chain Management KW - Informationssicherheit KW - Supply Chain KW - Risk Management KW - Coverage KW - Cybersecurity KW - Standard Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15633 ER - TY - THES A1 - Raich, Krispin T1 - Multimodal Data Space for Cooperative Intelligent Transport Systems N2 - Modern Cooperative Intelligent Transport Systems (C-ITSs) are comprehensive applications that must cope with a multitude of challenges while meeting strict service and security standards. One of these challenges is a fast, secure, reliable, and universal way to store and exchange data in such a traffic system. Furthermore, multimodal scenarios where different types of vehicles (e.g., cars and Unmanned Aerial System) interact with each other, are increasingly emerging. To overcome these challenges, this thesis presents a set of key innovations to establish a multimodal capable data space for transport application. Therefore, a multimodal optimized geographic model is presented, called SpatialJSON, that is capable of depicting two- and three-dimensional geometries. To accomplish this feat, SpatialJSON extends the popular GeoJSON format with two new data types: area and corridor. Exchanging, managing, and storing data is handled in a novel data-centric middleware, called Large Scale Multimodal Data Processing Middleware for Intelligent Transport Systems (LDPM). This LDPM uses cryptographic- and trust-based schemas to allow secure data exchange and provide data quality assessment. Furthermore, a service architecture is introduced, that fulfils modern service requirements. Trust management is also another essential part of a C-ITS. Hence, a novel scheme to describe traffic related evidence in a multimodal environment is introduced. This schema allows assessing arbitrary traffic related data. This information is then processed in a specialized and modified Bayesian Inference (BI) function. Subsequently, a comprehensive data centric trust management method is introduced. Finally, a use case is presented that relies on the aforementioned technologies to collect data in a hazardous environmental. This data is then distributed and managed via the LDPM, and finally visualized. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15496 ER - TY - THES A1 - Julka, Sahib T1 - Towards Data Efficiency and Controllable Representations for Deep Learning in Resource-Constrained Domains N2 - The deployment of artificial intelligence (AI) in specialised domains such as planetary science and healthcare, as well as in low-resource NLP settings, faces two fundamental challenges: label scarcity and data scarcity. Label scarcity stems from the high cost of expert annotation, the scarcity of domain experts, and the infeasibility of crowdsourcing, particularly in complex tasks requiring specialised knowledge. In parallel, data scarcity stems from the inherent difficulty of acquiring sufficient raw data, whether due to limited observational opportunities, environmental and technical barriers, or stringent privacy constraints. Together, these limitations impede the broader adoption of AI in these fields. Many existing approaches to label efficiency, such as active learning, rely on problem-specific heuristics and often, as a design choice, employ naive uncertainty estimations—typically at the instance level. However, such methods can lead to redundant or suboptimal sample selection by ignoring structural data properties and failing to account for representational diversity. In practice, they often perform no better than random sampling. For data synthesis, generative models face their own set of challenges. Despite their promise for synthetic data generation, these models frequently lack mechanisms to disentangle generative factors at the representation level, limiting their controllability. Additionally, standardised evaluation metrics to assess the quality of disentanglement remain underdeveloped, limiting their practical utility. These limitations highlight the need for advancements in data-efficient machine learning and controllable generative modelling, focusing on domain-specific validity and rigorous evaluation. This thesis contributes to addressing these challenges by proposing tailored solutions in two key directions. First, for data-efficient learning, a deep active learning (DAL) framework is introduced to enhance label efficiency by prioritising the most informative samples for annotation. Unlike traditional per-sample approaches, this framework aggregates uncertainty across larger data segments—such as orbital intervals in planetary science—allowing it to capture contextual variations. This method reduces labelled data requirements by up to 90% in the case of boundary crossing detection at Mercury’s magnetosphere. To further improve sampling diversity, a GAN-based concept drift detection method is integrated into the DAL framework, leveraging uncertainty and diversity together to offer a sampling method that outperforms random sampling. Additionally, foundation models such as the Segment Anything Model (SAM) are employed for zero-shot annotation to generate high-quality pseudo-labels, which are subsequently used to train a domain-specific model via knowledge distillation. This approach significantly enhances data efficiency, reducing the need for annotated samples several times over in the tested scenario of image segmentation for geological mapping. Furthermore, large language models (LLMs) are explored as active annotators for linguistic tasks in low-resource languages, achieving near-baseline performance while reducing annotation costs by up to 40x. Second, the thesis investigates methods to induce controllability in generative models, enabling the production of high-fidelity, controllable synthetic data. Conditional generative adversarial networks (CGANs) and disentangled representation learning techniques (DRL) are explored, particularly in the context of pedestrian trajectory prediction in the mobility domain, where controlled synthesis of diverse motion patterns is critical. Additionally, the work examines existing metrics for evaluating disentanglement and identifies critical limitations in them. A novel metric, the Exclusivity Disentanglement Index (EDI), is proposed as an improved standardised measure. Based on the principle of exclusivity in factor-code relationships, this metric offers advantages over existing alternatives in terms of efficiency and robustness. By advancing data-efficient learning and controllable generation strategies, this thesis aims to bridge the gap between AI’s vast potential and its practical adoption in resource-constrained environments. These contributions pave the way for transformative applications in planetary science, healthcare, and beyond, where label and data scarcity have long been barriers to progress. KW - artificial intelligence KW - deep active learning KW - label scarcity KW - data scarcity Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-16030 ER - TY - THES A1 - Wilhelm, Sebastian T1 - Emergency Detection in Private Households Utilizing Existing Data Sources for Human Activity Event Recognition N2 - In an aging society, the need for efficient emergency detection systems in smart homes is becoming increasingly important. Over 30% of those aged 65 and older experience at least one fall per year, often resulting in the inability to rise without assistance, leading to ‘long lies’ lasting hours or even days. Systems for detecting such emergency events usually rely on wearable sensors or specific installations of ambient sensors, which can be intrusive and complex, hindering acceptance. This thesis proposes a novel approach that utilizes existing digital data sources within the residential infrastructure to detect human activities and identify potential emergencies. A survey identifies 44 potential data sources in private households for recognizing human activity. However, extracting activity information often requires complex preprocessing. In this thesis, methodologies are developed for three of these data sources to highlight practical applications: Smart Power Meters, Smart Water Meters, and Home Weather Stations. It is shown that detecting human activities using these sources is feasible in a practical environment, although accuracy and reliability vary. Notably, Smart Water Meters demonstrate high reliability, with a precision of 0.86 and a recall of 1.00, making them particularly suitable for emergency detection. Existing emergency detection methods are not designed to handle uncertain activity data. This thesis introduces a novel approach based on probabilistic activity information, employing an Inactivity Score that provides a probabilistic weighting of inactivity periods based on the reliability of sensor measurements. By analyzing historical Inactivity Scores, anomalies that potentially represent an emergency can be identified. Evaluations across seven datasets show this approach outperforms existing methods, achieving a mean time to detect emergencies of approximately 05:23:28 hours and producing 0.09 false positives per day under noise-free conditions. Moreover, unlike related approaches, the proposed method remains effective with noisy data. This thesis demonstrates that emergencies in private households can be detected using existing data sources from the home infrastructure, offering a cost-effective and non-intrusive solution to enhance the safety and autonomy of the elderly at home. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15992 ER - TY - THES A1 - Hasenpflug, Mareike T1 - Slice sampling on Riemannian manifolds N2 - This thesis is concerned with hybrid slice samplers for approximate sampling of distributions on Riemannian manifolds. First for distributions on the Euclidean unit sphere, and then for distributions on general Riemannian manifolds we introduce a geodesic-based hybrid slice sampler, called geodesic slice sampler. Under mild regularity assumptions, we establish reversibility with respect to the target distribution for this sampler and positive semi-definiteness of the corresponding operator. Moreover, on compact Riemannian manifolds we show uniform ergodicity with explicit constants for the geodesic slice sampler if the target distribution has a bounded density with respect to the Riemannian measure. As an important building block of this sampler, we provide an explicit expression for the shrinkage procedure proposed in (Neal, 2003) in terms of a Markov kernel. We establish that this kernel is reversible with respect to the uniform distribution on the target set and that its corresponding operator is positive semi-definite. Beyond the geodesic slice sampler, we apply these results also to elliptical slice sampling (Murray, Adams, MacKay, 2010) to obtain a proof for its reversibility with respect to the target distribution and positive semi-definiteness of the corresponding operator. KW - Markov chain Monte Carlo KW - Slice sampling KW - Riemannian manifolds Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15903 ER - TY - JOUR A1 - Gosh Dastidar, Kanishka A1 - Caelen, Olivier A1 - Granitzer, Michael T1 - Machine learning methods for credit card fraud detection : a survey JF - IEEE Access N2 - The widespread adoption of online payments has been accompanied by a significant increase in fraudulent activities, resulting in billions of dollars in financial losses. As payment providers aim to tackle this with various preventive mechanisms, fraudsters also continuously evolve their methods to remain indistinguishable from genuine actors. This necessitates sophisticated fraud detection tools to supplement these security mechanisms. As the volume of transactions taking place per day is in the millions, relying solely on human investigation is expensive and ultimately unfeasible, leading to an emergence of research into data driven or statistical methods for fraud detection. Over the last decade, this research has evolved to tackle the various particularities of the domain. These include the skewed nature of the data, the evolving user and fraud behavior, and the learning representations of the context in which a transaction takes place. This work aims to provide the community with an in-depth overview of the different directions in which recent research on online fraud detection has focused. We develop a taxonomy of the domain based on these directions and organize our analysis accordingly. For each area, we focus on significant methodological advancements and highlight limitations or gaps in the current state-of-the-art solutions. Through our analysis, it emerges that one of the primary limiting factors that many researchers face is the lack of availability of high-quality credit card data. Therefore, we provide a first step in addressing this issue in the form of a data generation framework using generative adversarial networks (GANs). We hope that this survey serves as a foundation for researchers who want to address the multi-faceted problem of credit card fraud detection. KW - fraud detection KW - machine learning KW - neural networks KW - synthetic data Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-15796 VL - 2024 IS - 12 SP - 158939 EP - 158965 PB - IEEE CY - New York ER - TY - JOUR A1 - Lukasczyk, Stephan A1 - Kroiß, Florian A1 - Fraser, Gordon T1 - An empirical study of automated unit test generation for Python JF - Empirical Software Engineering N2 - Various mature automated test generation tools exist for statically typed programming languages such as Java. Automatically generating unit tests for dynamically typed programming languages such as Python, however, is substantially more difficult due to the dynamic nature of these languages as well as the lack of type information. Our P YNGUIN framework provides automated unit test generation for Python. In this paper, we extend our previous work on P YNGUIN to support more aspects of the Python language, and by studying a larger variety of well-established state of the art test-generation algorithms, namely DynaMOSA, MIO, and MOSA. Furthermore, we improved our P YNGUIN tool to generate regression assertions, whose quality we also evaluate. Our experiments confirm that evolutionary algorithms can outperform random test generation also in the context of Python, and similar to the Java world, DynaMOSA yields the highest coverage results. However, our results also demonstrate that there are still fundamental remaining issues, such as inferring type information for code without this information, currently limiting the effectiveness of test generation for Python. KW - Dynamic typing KW - Python KW - Automated Test Generation Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2023081721042349746457 VL - 28 IS - 1 SP - 1 EP - 46 PB - Springer Nature CY - Berlin ER - TY - JOUR A1 - Trautsch, Alexander A1 - Erbel, Johannes A1 - Herbold, Steffen A1 - Grabowski, Jens T1 - What really changes when developers intend to improve their source code: a commit-level study of static metric value and static analysis warning changes JF - Empirical Software Engineering KW - Static code analysis KW - Quality evolution KW - Software metrics KW - Software quality Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2023032321174386000821 VL - 28 IS - 2 SP - 1 EP - 40 PB - Springer Nature CY - Berlin ER - TY - JOUR A1 - Mironchenko, Andrii T1 - Well-posedness and properties of the flow for semilinear evolution equations JF - Mathematics of Control, Signals, and Systems N2 - We derive conditions for well-posedness of semilinear evolution equations with unbounded input operators. Based on this, we provide sufficient conditions for such properties of the flow map as Lipschitz continuity, bounded-implies-continuation property, boundedness of reachability sets, etc. These properties represent a basic toolbox for stability and robustness analysis of semilinear boundary control systems. We cover systems governed by general C0 -semigroups, and analytic semigroups that may have both boundary and distributed disturbances. We illustrate our findings on an example of a Burgers’ equation with nonlinear local dynamics and both distributed and boundary disturbances. KW - Well-posedness KW - Evolution equations KW - Boundary control systems KW - Infinite-dimensional systems KW - Analytic systems Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2024022307494197431619 VL - 36 IS - 3 SP - 483 EP - 523 PB - Springer Nature CY - Berlin ER - TY - JOUR A1 - Herbold, Steffen A1 - Tunkel, Steffen T1 - Differential testing for machine learning: an analysis for classification algorithms beyond deep learning JF - Empirical Software Engineering N2 - Differential testing is a useful approach that uses different implementations of the same algorithms and compares the results for software testing. In recent years, this approach was successfully used for test campaigns of deep learning frameworks. There is little knowledge about the application of differential testing beyond deep learning. Within this article, we want to close this gap for classification algorithms. We conduct a case study using Scikit-learn, Weka, Spark MLlib, and Caret in which we identify the potential of differential testing by considering which algorithms are available in multiple frameworks, the feasibility by identifying pairs of algorithms that should exhibit the same behavior, and the effectiveness by executing tests for the identified pairs and analyzing the deviations. While we found a large potential for popular algorithms, the feasibility seems limited because, often, it is not possible to determine configurations that are the same in other frameworks. The execution of the feasible tests revealed that there is a large number of deviations for the scores and classes. Only a lenient approach based on statistical significance of classes does not lead to a huge amount of test failures. The potential of differential testing beyond deep learning seems limited for research into the quality of machine learning libraries. Practitioners may still use the approach if they have deep knowledge about implementations, especially if a coarse oracle that only considers significant differences of classes is sufficient. KW - Machine learning KW - Software testing KW - Differential testing Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2023033121421148821912 VL - 28 IS - 2 SP - 1 EP - 38 PB - Springer Nature CY - Berlin ER - TY - JOUR A1 - Rudolf, Daniel A1 - Schär, Philip T1 - Dimension-independent spectral gap of polar slice sampling JF - Statistics and Computing N2 - Polar slice sampling, a Markov chain construction for approximate sampling, performs, under suitable assumptions on the target and initial distribution, provably independent of the state space dimension. We extend the aforementioned result of Roberts and Rosenthal (Stoch Model 18(2):257–280, 2002) by developing a theory which identifies conditions, in terms of a generalized level set function, that imply an explicit lower bound on the spectral gap even in a general slice sampling context. Verifying the identified conditions for polar slice sampling yields a lower bound of 1/2 on the spectral gap for arbitrary dimension if the target density is rotationally invariant, log-concave along rays emanating from the origin and sufficiently smooth. The general theoretical result is potentially applicable beyond the polar slice sampling framework. KW - MCMC KW - Slice Sampling KW - Spectral gap Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2024011821064231531382 VL - 34 IS - 1 PB - Springer Nature CY - Berlin ER - TY - JOUR A1 - Weißgerber, Thomas A1 - Ben Amor, Mehdi A1 - Fellicious, Christofer A1 - Granitzer, Michael T1 - PyPads: Transparent Machine Learning Experiment Tracking JF - Datenbank-Spektrum N2 - Despite algorithmic advancements in the field of machine learning, a need for improvement in the infrastructure supporting machine learning development and research has become increasingly apparent. Machine learning experiments usually tend to be more ad-hoc in nature, and results are communicated most often in the form of a publication. Experimental details are often omitted due to size or time constraints, or simply because the complexity in terms of technical setup or parametrization became intractable. Even access to code bases, disregard important properties of the environment and experimental setup, like for example random generators or computing infrastructure. At the same time, tracking and communicating an often inherently exploratory scientific process is a task with considerable effort. We explored different venues to tackle these issues from a data science engineering point of view. The efforts resulted in PyPads, a framework providing an infrastructure to extend experimental setups with logging, communication and analysis features in a mostly non-intrusive way. PyPads can be extended to different Python-based frameworks, utilizing community driven, descriptive metadata in an effort to harmonize library specific logs in an ontology. Meanwhile, we also try to emphasize similarities to practices in software engineering, which have turned out to be essential in practical applications. KW - Machine Learning KW - Reproducibility KW - Open Science KW - Automated Logging KW - Python Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2024021511222778687954 VL - 24 IS - 1 SP - 53 EP - 62 PB - Springer Nature CY - Berlin ER - TY - THES A1 - Mexis, Nico T1 - A Comprehensive Comparison of Fuzzy Extractor Schemes Employing Different Error Correction Codes N2 - This thesis deals with fuzzy extractors, security primitives often used in conjunction with Physical Unclonable Functions (PUFs). A fuzzy extractor works in two stages: The generation phase and the reproduction phase. In the generation phase, an Error Correction Code (ECC) is used to compute redundant bits for a given PUF response, which are then stored as helper data, and a key is extracted from the response. Then, in the reproduction phase, another (possibly noisy) PUF response can be used in conjunction with this helper data to extract the original key. It is clear that the performance of the fuzzy extractor is strongly dependent on the underlying ECC. Therefore, a comparison of ECCs in the context of fuzzy extractors is essential in order to make them as suitable as possible for a given situation. It is important to note that due to the plethora of various PUFs with different characteristics, it is very unrealistic to propose a single metric by which the suitability of a given ECC can be measured. First, we give a brief introduction to the topic, followed by a detailed description of the background of the ECCs and fuzzy extractors studied. Then, we summarise related work and describe an implementation of the ECCs under consideration. Finally, we carry out the actual comparison of the ECCs and the thesis concludes with a summary of the results and suggestions for future work. N2 - Diese Arbeit befasst sich mit Fuzzy Extractors, Sicherheitsprimitiven, die häufig in Verbindung mit Physical Unclonable Functions (PUFs) verwendet werden. Ein Fuzzy Extractor arbeitet in zwei Phasen: Der Generierungsphase und der Reproduktionsphase. In der Generierungsphase wird ein Fehlerkorrekturverfahren (ECC) verwendet, um redundante Bits für eine gegebene PUF-Antwort zu berechnen, die dann als Hilfsdaten gespeichert werden, und ein Schlüssel wird aus der Antwort extrahiert. In der Reproduktionsphase kann dann eine andere (möglicherweise verrauschte) PUF-Antwort zusammen mit diesen Hilfsdaten verwendet werden, um den ursprünglichen Schlüssel zu extrahieren. Es ist klar, dass die Leistung des Fuzzy Extractors stark von der Leistung des zugrunde liegenden ECC abhängt. Daher ist es unerlässlich, ECCs in Verbindung mit Fuzzy Extractors zu vergleichen, um sie für eine bestimmte Situation so geeignet wie möglich zu machen. Es ist wichtig, darauf hinzuweisen, dass es aufgrund der Vielzahl verschiedener PUFs mit unterschiedlichen Eigenschaften sehr unrealistisch ist, eine einzige Metrik vorzuschlagen, mit der die Eignung eines bestimmten ECCs gemessen werden kann. Wir beginnen mit einer kurzen Einführung in das Thema, gefolgt von einer detaillierten Beschreibung des Hintergrunds der untersuchten ECCs und Fuzzy Extractors. Anschließend fassen wir verwandte Arbeiten zusammen und beschreiben eine Implementierung der untersuchten ECCs. Schließlich führen wir den eigentlichen Vergleich der ECCs durch und schließen die Arbeit mit einer Zusammenfassung der Ergebnisse und Vorschlägen für zukünftige Arbeiten ab. T2 - Ein umfassender Vergleich von Fuzzy Extractors unter Verwendung verschiedener Fehlerkorrekturverfahren KW - Fuzzy extractor KW - Error correction KW - Vorwärtsfehlerkorrektur KW - Codierungstheorie KW - Physical unclonable function KW - Biometrie Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-12914 VL - 2023 ER - TY - JOUR A1 - Erdogan, Gülsah A1 - Hassen, Wiem Fekih T1 - Charging scheduling of hybrid energy storage systems for EV charging stations JF - Energies N2 - The growing demand for electric vehicles (EV) in the last decade and the most recent European Commission regulation to only allow EV on the road from 2035 involved the necessity to design a cost-effective and sustainable EV charging station (CS). A crucial challenge for charging stations arises from matching fluctuating power supplies and meeting peak load demand. The overall objective of this paper is to optimize the charging scheduling of a hybrid energy storage system (HESS) for EV charging stations while maximizing PV power usage and reducing grid energy costs. This goal is achieved by forecasting the PV power and the load demand using different deep learning (DL) algorithms such as the recurrent neural network (RNN) and long short-term memory (LSTM). Then, the predicted data are adopted to design a scheduling algorithm that determines the optimal charging time slots for the HESS. The findings demonstrate the efficiency of the proposed approach, showcasing a root-mean-square error (RMSE) of 5.78% for real-time PV power forecasting and 9.70% for real-time load demand forecasting. Moreover, the proposed scheduling algorithm reduces the total grid energy cost by 12.13%. KW - scheduling optimization KW - HESS KW - PV power KW - load demand KW - RNN KW - LSTM KW - GRU KW - cost reduction Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-14128 VL - 2023 IS - 16 PB - MDPI CY - Basel ER - TY - JOUR A1 - Frühwirth, Lorenz A1 - Juhos, Michael A1 - Prochno, Joscha T1 - The large deviation behavior of lacunary sums JF - Monatshefte für Mathematik N2 - We study the large deviation behavior of lacunary sums (Sn /n)n∈N with Sn :=∑[k=1...n] f (a(k)U), n ∈ |N, where U is uniformly distributed on [0, 1], (a(k))k∈|N is an Hadamard gap sequence, and f : |R → |R is a 1-periodic, (Lipschitz-)continuous mapping. In the case of large gaps, we show that the normalized partial sums satisfy a large deviation principle at speed n and with a good rate function which is the same as in the case of independent and identically distributed random variables U(k), k ∈ |N, having uniform distribution on [0, 1]. When the lacunary sequence (a(k))k∈|N is a geometric progression, then we also obtain large deviation principles at speed n, but with a good rate function that is different from the independent case, its form depending in a subtle way on the interplay between the function f and the arithmetic properties of the gap sequence. Our work generalizes some results recently obtained by Aistleitner, Gantert, Kabluchko, Prochno, and Ramanan [Large deviation principles for lacunary sums, preprint, 2020] who initiated this line of research for the case of lacunary trigonometric sums. KW - Hadamard gap sequence KW - Large deviation principle KW - Large gap condition KW - Geometric progression Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2022081723261050522140 VL - 2022 IS - 199 SP - 113 EP - 133 PB - Springer Nature CY - Berlin ER - TY - JOUR A1 - Harks, Tobias A1 - Schwarz, Julian T1 - Generalized Nash equilibrium problems with mixed-integer variables JF - Mathematical Programming N2 - We consider generalized Nash equilibrium problems (GNEPs) with non-convex strategy spaces and non-convex cost functions. This general class of games includes the important case of games with mixed-integer variables for which only a few results are known in the literature. We present a new approach to characterize equilibria via a convexification technique using the Nikaido–Isoda function. To any given instance of the GNEP, we construct a set of convexified instances and show that a feasible strategy profile is an equilibrium for the original instance if and only if it is an equilibrium for any convexified instance and the convexified cost functions coincide with the initial ones. We develop this convexification approach along three dimensions: We first show that for quasi-linear models, where a convexified instance exists in which for fixed strategies of the opponent players, the cost function of every player is linear and the respective strategy space is polyhedral, the convexification reduces the GNEP to a standard (non-linear) optimization problem. Secondly, we derive two complete characterizations of those GNEPs for which the convexification leads to a jointly constrained or a jointly convex GNEP, respectively. These characterizations require new concepts related to the interplay of the convex hull operator applied to restricted subsets of feasible strategies and may be interesting on their own. Note that this characterization is also computationally relevant as jointly convex GNEPs have been extensively studied in the literature. Finally, we demonstrate the applicability of our results by presenting a numerical study regarding the computation of equilibria for three classes of GNEPs related to integral network flows and discrete market equilibria. KW - Generalized Nash equilibrium problem KW - Mixed-integer nonlinear problem KW - Non-convex games KW - Complementarity and equilibrium problems and variational inequalities (finite dimensions) KW - Mixed integer programming KW - Noncooperative games Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2405152117292.567771401889 SN - 0025-5610 SN - 1436-4646 VL - 209 IS - 1 SP - 231 EP - 277 PB - Springer Berlin Heidelberg CY - Berlin/Heidelberg ER - TY - JOUR A1 - Kreuzer, Martin A1 - Long, Le Ngoc A1 - Robbiano, Lorenzo T1 - Re-embeddings of affine algebras via Gröbner fans of linear ideals JF - Beiträge zur Algebra und Geometrie / Contributions to Algebra and Geometry N2 - Given an affine algebra R=K[x1,⋯,xn]/Iover a field  K , where I is an ideal in the polynomial ring P=K[x1,⋯,xn], we examine the task of effectively calculating re-embeddings of  I , i.e., of presentations R=P′/I′such that P′=K[y1,⋯,ym]has fewer indeterminates. For cases when the number of indeterminates  n is large and Gröbner basis computations are infeasible, we have introduced the method of Z -separating re-embeddings in Kreuzer et al. (J Algebra Appl 21, 2022) and Kreuzer, et al. (São Paulo J Math Sci, 2022). This method tries to detect polynomials of a special shape in  I which allow us to eliminate the indeterminates in the tuple  Z by a simple substitution process. Here we improve this approach by showing that suitable candidate tuples  Z can be found using the Gröbner fan of the linear part of  I . Then we describe a method to compute the Gröbner fan of a linear ideal, and we improve this computation in the case of binomial linear ideals using a cotangent equivalence relation. Finally, we apply the improved technique in the case of the defining ideals of border basis schemes. KW - Re-embedding KW - Optimal embedding KW - Gröbner fan KW - Cotangent space KW - Border basis scheme Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2024041316352253862922 SN - 0138-4821 SN - 2191-0383 VL - 65 IS - 4 SP - 827 EP - 851 PB - Springer Berlin Heidelberg CY - Berlin/Heidelberg ER - TY - JOUR A1 - Prochno, Joscha A1 - Rudolf, Daniel T1 - The minimal spherical dispersion JF - The Journal of Geometric Analysis N2 - We prove upper and lower bounds on the minimal spherical dispersion, improving upon previous estimates obtained by Rote and Tichy in (Anz Österreich Akad Wiss Math Nat Kl 132:3–10, 1995). In particular, we see that the inverse N(ε,d)of the minimal spherical dispersion is, for fixed ε>0, linear in the dimension d of the ambient space. We also derive upper and lower bounds on the expected dispersion for points chosen independently and uniformly at random from the Euclidean unit sphere. In terms of the corresponding inverse N~(ε,d), our bounds are optimal with respect to the dependence on ε. KW - Dispersion KW - Expected dispersion KW - Spherical cap KW - Spherical dispersion KW - VC-dimension Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2405020842543.936733306281 SN - 1050-6926 SN - 1559-002X VL - 34 IS - 3 PB - Springer US CY - New York ER - TY - THES A1 - Klement, Felix T1 - Strengthening Security Foundations in Next-G Wireless Telecommunication Systems N2 - Digital transformation fundamentally impacts our everyday lives and creates significant efficiency gains in the economy. At the same time, however, it is also increasing the complexity of wireless networks, particularly in the case of the sixth generation (6G) mobile communications standard. The use of different technologies in these networks poses an increasing challenge and increases the risk of security threats and vulnerabilities. Wireless communication networks are particularly vulnerable to cyber attacks as they are an integral part of critical infrastructures. Robust methods must, therefore, be developed to overcome these challenges. Consequently, this dissertation is focused on the security fundamentals of next-generation (Next-G) wireless telecommunication systems. It addresses the security challenges resulting from emerging and innovative concepts within these systems. We use case studies for in-depth investigation and analysis, with a particular focus on the Open Radio Access Network (O-RAN) approach. The aim of this concept is to enable open and interoperable network architectures, in contrast to traditional RAN systems, which are often proprietary and manufacturer-specific. In this respect, it is essential to address fundamental questions, like the efficient assessment of the threat landscape, the impact of potential attacks, and the mechanisms that can be used to ensure security at the system level. Initially, an empirical approach is developed to analyze threats within telecommunications systems, such as the O-RAN. The procedure we have developed enables automated, programmatically executable vulnerability management. This methodology is further enhanced by integrating Natural Language Processing (NLP), leading to the creation of a fully automated, iteratively executable framework for security analysis within O-RANs. The framework allows for the direct incorporation of our methods into the deployment process, facilitating rapid and efficient comparison of all components against the latest security vulnerabilities. The current approach of fully deploying all components in virtualized environments, such as cloud infrastructures, introduces new and unprecedented security challenges. In response, we investigate current deployment strategies within the O-RAN infrastructure and establish best practices to mitigate these security issues. In the course of the dissertation, we identify security vulnerabilities in wireless telecommunication systems by executing different attack scenarios. We present a detailed procedure for carrying out the attacks as well as effective methodologies for detecting or avoiding the vulnerabilities we have identified. In the first study, we analyze the security of a key component, the Near-Real-Time RAN Intelligent Controller (Near-RT RIC), within O-RAN. We show how a subscription Denial of Service (DoS) attack can render current implementations of this component unusable. In the second analysis, we investigate the robustness of new standards in wireless networks against jamming attacks using the open-source connectivity standard Matter. The final section of this dissertation explores innovative security research approaches for enhancing the system security of future communication systems. Initially, a novel concept is introduced that facilitates the comprehensive and efficient management and assurance of security within O-RAN systems through the use of Security Platforms (SPs). Furthermore, two developed methodologies for this approach are presented: firstly, a method for programmatically analyzing eXtended Applications (xApps) to identify vulnerabilities, and secondly, an approach for conducting comparative assessments of these vulnerabilities. Additionally, a strategy is proposed to ensure that only secure xApps, such as those that have been pre-tested, are deployed for use in Near-RT RIC. Overall, this dissertation makes an important contribution to the research of security principles for next-generation wireless telecommunication systems. With the help of our approaches for a better and more concrete assessment of threats in such networks, we directly contribute to a clearer and better manageable picture of the vulnerability landscape. Our two publications on vulnerability research also provide valuable insights for securing future problems in the respective areas. In summary, with our approaches to system security, with which security principles can be implemented and integrated into modern system approaches such as O-RAN, we contribute to ensuring a secure transition to 6G. KW - Security KW - Next-G KW - 6G KW - Open RAN Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-18669 ER - TY - JOUR A1 - Dang, Duc-Cuong A1 - Opris, Andre A1 - Sudholt, Dirk T1 - Crossover can guarantee exponential speed-ups in evolutionary multi-objective optimisation JF - Artificial Intelligence (Online ISSN: 1872-7921) N2 - Evolutionary algorithms are popular algorithms for multi-objective optimisation (also called Pareto optimisation) as they use a population to store trade-offs between different objectives. Despite their popularity, the theoretical foundation of multi-objective evolutionary optimisation (EMO) is still in its early development. Fundamental questions such as the benefits of the crossover operator are still not fully understood. We provide a theoretical analysis of the well-known EMO algorithms GSEMO and NSGA-II to showcase the possible advantages of crossover: we propose classes of “royal road” functions on which these algorithms cover the whole Pareto front in expected polynomial time if crossover is being used. But when disabling crossover, they require exponential time in expectation to cover the Pareto front. The latter even holds for a large class of black-box algorithms using any elitist selection and any unbiased mutation operator. Moreover, even the expected time to create a single Pareto-optimal search point is exponential. We provide two different function classes, one tailored for one-point crossover and another one tailored for uniform crossover, and we show that some immune-inspired hypermutations cannot avoid exponential optimisation times. Our work shows the first example of an exponential performance gap through the use of crossover for the widely used NSGA-II algorithm and contributes to a deeper understanding of its limitations and capabilities. KW - Evolutionary computation KW - Runtime analysis KW - Recombination KW - Multi-objective optimisation KW - Unbiased black-box algorithms KW - Hypermutation Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-18732 VL - 2025 IS - 330 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Kreuzer, Martin A1 - Walsh, Florian T1 - Computing the binomial part of a polynomial ideal JF - Journal of Symbolic Computation (Online ISSN: 1095-855X) N2 - Given an ideal I in a polynomial ring K[x1,...,xn] over a field K, we present a complete algorithm to compute the binomial part of I, i.e., the subideal Bin(I) of I generated by all monomials and binomials in I. This is achieved step-by-step. First we collect and extend several algorithms for computing exponent lattices in different kinds of fields. Then we generalize them to compute exponent lattices of units in 0-dimensional K-algebras, where we have to generalize the computation of the separable part of an algebra to non-perfect fields in characteristic p. Next we examine the computation of unit lattices in finitely generated K-algebras, as well as their associated characters and lattice ideals. This allows us to calculate Bin(I) when I is saturated with respect to the indeterminates by reducing the task to the 0-dimensional case. Finally, we treat the computation of Bin(I) for general ideals by computing their cellular decomposition and dealing with finitely many special ideals called (s,t)-binomial parts. All algorithms have been implemented in SageMath. KW - binomial part KW - binomial ideal KW - exponent lattice KW - cellular decomposition Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-18708 VL - 2024 IS - 124 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Frühwirth, Lorenz A1 - Prochno, Joscha T1 - Sanov-type large deviations and conditional limit theorems for high-dimensional Orlicz balls JF - Journal of Mathematical Analysis and Applications (Online ISSN: 1096-0813) N2 - In this paper, we prove a Sanov-type large deviation principle for the sequence of empirical measures of vectors chosen uniformly at random from an Orlicz ball. From this level-2 large deviation result, in a combination with Gibbs conditioning, entropy maximization and an Orlicz version of the Poincaré-Maxwell-Borel lemma, we deduce a conditional limit theorem for high-dimensional Orlicz balls. In more geometric parlance, the latter shows that if V1 and V2 are Orlicz functions, then random points in the V1-Orlicz ball, conditioned on having a small V2-Orlicz radius, look like an appropriately scaled V2-Orlicz ball. In fact, we show that the limiting distribution in our Poincaré-Maxwell-Borel lemma, and thus the geometric interpretation, undergoes a phase transition depending on the magnitude of the V2-Orlicz radius. KW - Entropy maximization KW - Gibbs conditioning principle KW - Large deviation principle KW - Orlicz space KW - Poincaré-Maxwell-Borel lemma KW - Sanov's theorem Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-18723 VL - 2024 IS - 536,1 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Peña Ferrández, Juan Manuel A1 - Sauer, Thomas T1 - Stabilized recovery and model reduction for multivariate exponential polynomials JF - Journal of Symbolic Computation (Online ISSN: 1095-855X) N2 - Recovery of multivariate exponential polynomials, i.e., the multivariate version of Prony's problem, can be stabilized by using more than the minimally needed multiinteger samples of the function. We present an algorithm that takes into account this extra information and prove a backward error estimate for the algebraic recovery method SMILE. In addition, we give a method to approximate data by an exponential polynomial sequence of a given structure as a step in the direction of multivariate model reduction. KW - Prony's method KW - Gröbner basis KW - Backwards error KW - Model reduction Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-18748 VL - 2024 IS - 125 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Kabluchko, Zakhar A1 - Prochno, Joscha A1 - Sonnleitner, Mathias T1 - A probabilistic approach to Lorentz balls l(^n)(q,1) JF - Journal of Functional Analysis (Online ISSN: 1096-0783) N2 - We develop a probabilistic approach to study the volumetric and geometric properties of unit balls |B(^n)(q,1) of finite-dimensional Lorentz sequence spaces l(^n)(q,1). More precisely, we show that the empirical distribution of a random vector X^(n) uniformly distributed on its volume normalized unit ball converges weakly to a compactly supported symmetric probability distribution with explicitly given density; as a consequence we obtain a weak Poincaré-Maxwell-Borel principle for any fixed number k in |N of coordinates of X^(n) as n grows infinitly. Moreover, we prove a central limit theorem for the largest coordinate of X^(n), demonstrating a quite different behavior than in the case of the l(^n)(q) balls, where a Gumbel distribution appears in the limit. Finally, we prove a Schechtman-Schmuckenschläger type result for the asymptotic volume of intersections of volume normalized l(^n)(q,1) and l(^n)(p) balls. KW - Central limit theorem KW - Concentration of measure KW - Convex body KW - Maximum entropy principle Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-18878 VL - 2025 IS - 288, 1 PB - Elsevier CY - Amsterdam ER - TY - THES A1 - Zerhoudi, Saber T1 - User Simulation in Interactive Information Retrieval : methods and frameworks for simulating complex search behavior N2 - Modern information retrieval (IR) systems, including web search engines and digital libraries, face challenges in simulating realistic user search behavior. Evolving interaction patterns and the integration of AI-powered interfaces make these challenges even harder. Traditional evaluation methods struggle to capture the dynamic nature of user interactions, particularly in complex search tasks and multi-stage information-seeking processes. User simulation offers a promising solution, providing a controlled environment for experimentation and allowing customization to model specific user behaviors and task contexts. This research develops advanced techniques for user simulation in IR, creating more realistic and dynamic models than were previously possible. Key contributions include new methods for representing query reformulation, modeling how information needs change, and measuring the impact of different search environments on simulated user behavior. Specifically, this work introduces contextual Markov models, cognitive state models, and embedding space alignment techniques to accurately represent interactive search behavior. Beyond model development, new evaluation methods and metrics are proposed for assessing the quality of simulated search sessions. These include statistical comparisons of session characteristics and classification-based approaches to distinguish between simulated and real user behavior. Additionally, this work leverages emerging technologies, such as large language models (LLMs) and retrieval-augmented generation, to improve the realism of user search behavior simulation. The practical outcome of this research is a modular and extensible simulation framework. This framework incorporates advanced techniques like user type-specific Markov models, advanced query generation using LLMs, and conversational user models. KW - Information retrieval KW - user simulation KW - evaluation KW - simulation framework Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-18936 N1 - Die Leerseiten iii, iv, vi(i), x, xi sind nicht Teil des Dokuments. ER - TY - JOUR A1 - Müller-Gronbach, Thomas A1 - Yaroslavtseva, Larisa T1 - On the complexity of strong approximation of stochastic differential equations with a non-Lipschitz drift coefficient JF - Journal of Complexity (Online ISSN: 1090-2708) N2 - We survey recent developments in the field of complexity of pathwise approximation in p-th mean of the solution of a stochastic differential equation at the final time based on finitely many evaluations of the driving Brownian motion. First, we briefly review the case of equations with globally Lipschitz continuous coefficients, for which an error rate of at least 1/2 in terms of the number of evaluations of the driving Brownian motion is always guaranteed by using the equidistant Euler-Maruyama scheme. Then we illustrate that giving up the global Lipschitz continuity of the coefficients may lead to a non-polynomial decay of the error for the Euler-Maruyama scheme or even to an arbitrary slow decay of the smallest possible error that can be achieved on the basis of finitely many evaluations of the driving Brownian motion. Finally, we turn to recent positive results for equations with a drift coefficient that is not globally Lipschitz continuous. Here we focus on scalar equations with a Lipschitz continuous diffusion coefficient and a drift coefficient that satisfies piecewise smoothness assumptions or has fractional Sobolev regularity and we present corresponding complexity results. KW - Stochastic differential equations KW - Non-Lipschitz drift coefficient KW - Strong approximation in p-th mean KW - Complexity KW - Lower error bounds KW - Error rates Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-18819 VL - 2024 IS - 85 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Fekih Hassen, Wiem A1 - Schoppik, Luis A1 - Schiegg, Sascha A1 - Gerl, Armin T1 - Power management approach of hybrid energy storage system for electric vehicle charging stations JF - Smart Cities N2 - The applicability of Hybrid Energy Storage Systems (HESSs) has been shown in multiple application fields, such as Charging Stations (CSs), grid services, and microgrids. HESSs consist of an integration of two or more single Energy Storage Systems (ESSs) to combine the benefits of each ESS and improve the overall system performance. In this work, we propose a novel power management controller called the Hybrid Controller for the efficient HESS’s charging and discharging, considering the State of Charge (SoC) of the HESS and the dynamic supply and load. The Hybrid Controller optimises the use of the HESS, i.e., minimises the amount of energy drawn from and discharged to the grid, thus utilising and prioritising the provided Photovoltaic (PV) power. The performance of our proposal was assessed via simulation using various evaluation metrics, i.e., Autarky, charge/discharge cycle, and Self-Consumption (SC), where we defined 24 scenarios in different locations in Germany. KW - HESS KW - RFB KW - lithium battery KW - power distribution KW - OpenEMS KW - real load dataset Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:m347-opus-6045 SN - 2624-6511 VL - 7 (2024) IS - 6 SP - 4025 EP - 4051 PB - MDPI CY - Basel ER - TY - JOUR A1 - Epperlein, Jeremias A1 - Wirth, Fabian T1 - The joint spectral radius is pointwise Hölder continuous JF - Linear Algebra and its Applications N2 - We show that the joint spectral radius is pointwise Hölder continuous. In addition, the joint spectral radius is locally Hölder continuous for ε-inflations. In the two-dimensional case, local Hölder continuity holds on the matrix sets with positive joint spectral radius. KW - Joint spectral radius KW - Hölder continuity KW - Extremal norm Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19140 SN - 1873-1856 VL - 2025 IS - 704 SP - 92 EP - 122 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Hackl, Veronika A1 - Müller, Alexandra Elena A1 - Granitzer, Michael A1 - Sailer, Maximilian T1 - Is GPT-4 a reliable rater? Evaluating consistency in GPT-4's text ratings JF - Frontiers in Education N2 - This study reports the Intraclass Correlation Coefficients of feedback ratings produced by OpenAI's GPT-4, a large language model (LLM), across various iterations, time frames, and stylistic variations. The model was used to rate responses to tasks related to macroeconomics in higher education (HE), based on their content and style. Statistical analysis was performed to determine the absolute agreement and consistency of ratings in all iterations, and the correlation between the ratings in terms of content and style. The findings revealed high interrater reliability, with ICC scores ranging from 0.94 to 0.99 for different time periods, indicating that GPT-4 is capable of producing consistent ratings. The prompt used in this study is also presented and explained. KW - artificial intelligence KW - GPT-4 KW - large language model KW - prompt engineering KW - feedback KW - higher education Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-18348 SN - 2504-284X VL - 2023 IS - 8 PB - Frontiers CY - Lausanne ER - TY - THES A1 - Fellicious, Christofer T1 - Bridging the gap: Applying machine learning techniques in digital forensics N2 - With the increasing adoption of virtualization technologies across various industries, virtual machines (VMs) offer cost-effective solutions for obtaining computing power without the burden of initial investment or ongoing maintenance. However, the widespread use of VMs also increases the risk of malicious actors attempting to gain unauthorized access due to the possibility of accessing the VMs via standard internet protocols. Virtual Machine Introspection (VMI) and Forensic Memory Analysis (FMA) are two key cybersecurity methods for addressing these threats. While FMA leverages digital forensic techniques to extract and analyse information from system memory to explain security incidents, VMI typically works with live systems, analysing running processes to detect real-time threats. Both approaches face a significant challenge known as the ”semantic gap,” which arises from the need to infer high-level system information from low-level data such as physical memory and CPU registers. This dissertation explores using machine learning to bridge the semantic gap in FMA and VMI applications. The research uses OpenSSH process heap dumps as a use-case to extract high-level structures, such as OpenSSH encryption keys, from raw process memory dumps. The study employs various techniques to isolate relevant memory sections, from basic memory chunking and entropy analysis to more advanced methods utilizing pointers and malloc headers. During this research study, we also identified the need for a foundation model in memory forensics. Foundation models are general purpose models trained on large amounts of data and users can later use these models to perform different tasks by finetuning the model. This research also addresses the challenge of detecting malware by analysing system-level API calls and employing custom feature engineering techniques. Given that the threat landscape is constantly evolving, we also investigate concept drift — a phenomenon where input data distribution changes affect predictive models’ performance. To mitigate the degradation in performance due to concept drift, we introduce a concept drift detection algorithm complemented by a custom sampling method that optimizes training data selection. This approach reduces the training dataset size by one-third, enhancing the efficiency of model training while maintaining high performance. KW - semantic gap KW - virtual machine introspection KW - forensic memory analysis Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-18473 ER - TY - JOUR A1 - Glock, Stefan A1 - Munhá Correia, David A1 - Sudakov, Benny T1 - Hamilton cycles in pseudorandom graphs JF - Advances in Mathematics N2 - Finding general conditions which ensure that a graph is Hamiltonian is a central topic in graph theory. An old and well-known conjecture in the area states that any d-regular n-vertex graph G whose second largest eigenvalue in absolute value λ(G) is at most d/C, for some universal constant C > 0, has a Hamilton cycle. In this paper, we obtain two main results which make substantial progress towards this problem. Firstly, we settle this conjecture in full when the degree d is at least a small power of n. Secondly, in the general case we show that λ(G) ≤ d/C(log n)1/3 implies the existence of a Hamilton cycle, improving the 20-year old bound of d/ log1−o(1) n of Krivelevich and Sudakov. We use in a novel way a variety of methods, such as a robust Pósa rotation-extension technique, the Friedman-Pippenger tree embedding with rollbacks and the absorbing method, combined with additional tools and ideas. Our results have several interesting applications. In particular, they imply the currently best-known bounds on the number of generators which guarantee the Hamiltonicity of random Cayley graphs, which is an important partial case of the well known Hamiltonicity conjecture of Lovász. They can also be used to improve a result of Alon and Bourgain on additive patterns in multiplicative subgroups. KW - Hamilton cycle KW - Hamiltonicity KW - Pseudorandom graph KW - Expander graph Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19151 VL - 2024 IS - 458 B PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Zubaer, Abdullah Al A1 - Granitzer, Michael A1 - Mitrović, Jelena T1 - Performance analysis of large language models in the domain of legal argument mining JF - Frontiers in Artificial Intelligence N2 - Generative pre-trained transformers (GPT) have recently demonstrated excellent performance in various natural language tasks. The development of ChatGPT and the recently released GPT-4 model has shown competence in solving complex and higher-order reasoning tasks without further training or fine-tuning. However, the applicability and strength of these models in classifying legal texts in the context of argument mining are yet to be realized and have not been tested thoroughly. In this study, we investigate the effectiveness of GPT-like models, specifically GPT-3.5 and GPT-4, for argument mining via prompting. We closely study the model's performance considering diverse prompt formulation and example selection in the prompt via semantic search using state-of-the-art embedding models from OpenAI and sentence transformers. We primarily concentrate on the argument component classification task on the legal corpus from the European Court of Human Rights. To address these models' inherent non-deterministic nature and make our result statistically sound, we conducted 5-fold cross-validation on the test set. Our experiments demonstrate, quite surprisingly, that relatively small domain-specific models outperform GPT 3.5 and GPT-4 in the F1-score for premise and conclusion classes, with 1.9% and 12% improvements, respectively. We hypothesize that the performance drop indirectly reflects the complexity of the structure in the dataset, which we verify through prompt and data analysis. Nevertheless, our results demonstrate a noteworthy variation in the performance of GPT models based on prompt formulation. We observe comparable performance between the two embedding models, with a slight improvement in the local model's ability for prompt selection. This suggests that local models are as semantically rich as the embeddings from the OpenAI model. Our results indicate that the structure of prompts significantly impacts the performance of GPT models and should be considered when designing them. KW - natural language processing (NLP) KW - argument mining KW - legal data KW - European Court of Human Rights (ECHR) KW - sequence classification KW - GPT-4 KW - ChatGPT KW - large language models Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-18326 SN - 2624-8212 VL - 2023 IS - 6 PB - Frontiers CY - Lausanne ER - TY - JOUR A1 - Kreuzer, Martin A1 - Linh, Tran N. K. A1 - Long, Le N. T1 - Differential theory of zero-dimensional schemes JF - Journal of Pure and Applied Algebra N2 - To study a 0-dimensional scheme |X in |P^n over a perfect field K, we use the module of Kähler differentials (Omega)(^1)(_{R/K}) of its homogeneous coordinate ring R and its exterior powers, the higher modules of Kähler differentials (Omega)(^m)(_{R/K}). One of our main results is a characterization of weakly curvilinear schemes |X by the Hilbert polynomials of the modules (Omega)(^m)(_{R/K}) which allows us to check this property algorithmically without computing the primary decomposition of the vanishing ideal of |X. Further main achievements are precise formulas for the Hilbert functions and Hilbert polynomials of the modules (Omega)(^m)(_{R/K}) for a fat point scheme |X which extend and settle previous partial results and conjectures. Underlying these results is a novel method: we first embed the homogeneous coordinate ring R into its truncated integral closure ~R. Then we use the corresponding map from the module of Kähler differentials (Omega)(^1)(_{R/K}) to (Omega)(^1)(_{~R/K}) to find a formula for the Hilbert polynomial HP((Omega)(^1)(_{R/K})) and a sharp bound for the regularity index ri((Omega)(^1)(_{R/K})). Next we extend this to formulas for the Hilbert polynomials HP((Omega)(^m)(_{R/K})) and bounds for the regularity indices of the higher modules of Kähler differentials. As a further application, we characterize uniformity conditions on |X using the Hilbert functions of the Kähler differential modules of |X and its subschemes. KW - Kähler differential module KW - Zero-dimensional scheme KW - Regularity index KW - Hilbert function KW - Curvilinear scheme KW - Fat point scheme Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19130 SN - 1873-1376 VL - 229 (2025) IS - 1 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Kreuzer, Martin A1 - Miasnikov, Alexei A1 - Walsh, Florian T1 - Decomposing finite Z-algebras JF - Journal of Algebra N2 - For a finite Z-algebra R, i.e., for a ring which is not necessarily associative or unitary, but whose additive group is finitely generated, we construct a decomposition of R/Ann(R) into directly indecomposable factors under weak hypotheses. The method is based on constructing and decomposing a ring of scalarsS, and then lifting the decomposition ofSto the bilinear map given by the multiplication of R, and finally to R/Ann(R). All steps of the construction are given as explicit algorithms and it is shown that the entire procedure has a probabilistic polynomial time complexity in the bit size of the input, except for the possible need to calculate the prime factorization of an integer. In particular, in the case when Ann(R)=0, these algorithms compute direct decompositions of R into directly indecomposable factors. KW - Algebra decomposition KW - Directly indecomposable factor KW - Bilinear map KW - Maximal ring of scalars KW - Primitive idempotent KW - Lie ring Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19184 SN - 1090-266X VL - 2025 IS - 664 B SP - 206 EP - 246 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Berger, Christian A1 - Rodrigues, Lívio A1 - Reiser, Hans P. A1 - Cogo, Vinícius A1 - Bessani, Alysson T1 - Chasing lightspeed consensus T2 - Middleware '24: Proceedings of the 25th International Middleware Conference N2 - Blockchain technology sparked renewed interest in planetary-scale Byzantine fault-tolerant (BFT) state machine replication (SMR). While recent works predominantly focused on improving the scalability and throughput of these protocols, few of them addressed latency. We present Mercury, a novel transformation to autonomously optimize the latency of quorum-based BFT consensus. Mercury employs a dual resilience threshold that enables faster transaction ordering when the system contains few faulty replicas. Mercury allows forming compact quorums that substantially accelerate consensus using a smaller resilience threshold. Nevertheless, Mercury upholds standard SMR safety and liveness guarantees with optimal resilience, thanks to its judicious use of a dual operation mode and BFT forensics techniques. Our experiments spread tens of replicas across continents and reveal that Mercury can order transactions with finality in less than 0.4s, half the time of a PBFT-like protocol (optimal in terms of number of communication steps and resilience) in the same network. Furthermore, Mercury matches the latency of running its base protocol on theoretically optimal internet links (transmitting at 67% of the speed of light). Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19106 SN - 979-8-4007-0623-3 VL - 2024 SP - 158 EP - 171 PB - ACM CY - New York ER - TY - JOUR A1 - Gishboliner, Lior A1 - Glock, Stefan A1 - Sgueglia, Amedeo T1 - Tight Hamilton cycles with high discrepancy JF - Combinatorics, Probability and Computing (1469-2163) N2 - In this paper, we study discrepancy questions for spanning subgraphs of k-uniform hypergraphs. Our main result is that, for any integers k ≥ 3 and r ≥ 2, any r-colouring of the edges of a k-uniform n-vertex hypergraph G with minimum (k−1)-degree δ(G) ≥ (1/2+o(1))n contains a tight Hamilton cycle with high discrepancy, that is, with at least n/r +� (n) edges of one colour. The minimum degree condition is asymptotically best possible and our theorem also implies a corresponding result for perfect matchings. Our tools combine various structural techniques such as Turán-type problems and hypergraph shadows with probabilistic techniques such as random walks and the nibble method. We also propose several intriguing problems for future research. KW - Discrepancy KW - tight Hamilton cycles KW - random walks KW - nibble method Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19166 SN - 1469-2163 VL - 34 (2025) IS - 4 SP - 565 EP - 584 PB - Cambridge University Press CY - Cambridge ER - TY - JOUR A1 - Chen, Yijia A1 - Müller, Moritz A1 - Yokoyama, Keita T1 - A parameterized halting problem, Δ0 truth and the MRDP theorem JF - The Journal of Symbolic Logic (ISSN 1943-5886) N2 - We study the parameterized complexity of the problem to decide whether a given natural number n satisfies a given Δ0-formula ϕ(x); the parameter is the size of ϕ. This parameterization focusses attention on instances where n is large compared to the size of ϕ.We show unconditionally that this problem does not belong to the parameterized analogue of AC0. From this we derive that certain natural upper bounds on the complexity of our parameterized problem imply certain separations of classical complexity classes. This connection is obtained via an analysis of a parameterized halting problem. Some of these upper bounds follow assuming that IΔ0 proves the MRDP theorem in a certain weak sense. KW - bounded arithmetical truth KW - parameterized halting KW - descriptive complexity KW - weak arithmetic KW - MRDP theorem Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19308 SN - 1943-5886 VL - 90 (2025) IS - 2 SP - 483 EP - 508 PB - Cambridge University Press CY - Cambridge ER - TY - JOUR A1 - Lechl, Michael A1 - de Meer, Hermann A1 - Fürmann, Tim T1 - A stochastic flexibility calculus for uncertainty-aware energy flexibility management JF - Applied Energy N2 - The increasing share of volatile renewables in power systems requires more reserves to balance forecast errors in renewable generation and power fluctuations. In contrast, common reserves such as gas-fired power plants are phased out, impeding the procurement of sufficient reserves. Alternative reserves, particularly on the demand side, such as battery storage systems, also exhibit some degree of freedom to deviate from their scheduled operating point to supply or consume more or less power, thus providing a flexibility potential. However, demand-side flexibility potentials are generally subject to uncertainties, and so is the generation of volatile renewables. The challenge is incorporating the uncertainties on both sides to procure sufficient (uncertain) flexibility potential in advance. Considering uncertainty is important to avoid additional, drastic measures in real-time to balance generation and demand, such as curtailing renewable generation or load shedding. This work presents a stochastic flexibility calculus that provides an indicator for computing the risk of insufficient flexibility potentials or, conversely, guarantees for sufficient flexibility potentials. Thus, the stochastic flexibility calculus contributes to overcoming the challenge of procuring sufficient flexibility potentials in renewable-based systems. An evaluation based on real data is performed using an example of a renewable energy community consisting of households equipped with photovoltaic power plants and battery storage systems. The newly introduced stochastic flexibility calculus computes the number of households that must operate their battery storage systems flexibly to balance forecast errors locally. The results show that the forecast method significantly influences this number. Some numerical results appear unexpected, as too many flexibility-friendly households can negatively impact the aggregated household flexibility potential. KW - Stochastic network calculus KW - Probabilistic flexibility guarantees KW - Power system flexibility KW - Renewable energy community KW - Uncertainty modeling KW - Battery storage system Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19233 VL - 2025 IS - 379 ER - TY - JOUR A1 - Baumann, Jakob A1 - Pfretzschner, Matthias A1 - Rutter, Ignaz T1 - Parameterized complexity of vertex splitting to pathwidth at most 1 JF - Theoretical Computer Science N2 - Motivated by the planarization of 2-layered straight-line drawings, we consider the problem of modifying a graph such that the resulting graph has pathwidth at most 1. The problem Pathwidth-One Vertex Explosion (POVE) asks whether such a graph can be obtained using at most 𝑘 vertex explosions, where a vertex explosion replaces a vertex 𝑣 by deg(𝑣) degree-1 vertices, each incident to exactly one edge that was originally incident to 𝑣. For POVE, we give an FPT algorithm with running time 𝑂(4𝑘 ⋅ 𝑚) and an 𝑂(𝑘2) kernel, thereby improving over the 𝑂(𝑘6) kernel by Ahmed et al. [2] in a more general setting. Similarly, a vertex split replaces a vertex 𝑣 by two distinct vertices 𝑣1 and 𝑣2 and distributes the edges originally incident to 𝑣 arbitrarily to 𝑣1 and 𝑣2. Analogously to POVE, we define the problem variant Pathwidth-One Vertex Splitting (POVS) that uses the split operation instead of vertex explosions. Here we obtain a linear kernel and an algorithm with running time 𝑂((6𝑘 + 12)𝑘 ⋅ 𝑚). This answers an open question by Ahmed et al. [2]. Finally, we consider the problem Π-VertexSplitting (Π-VS), which generalizes the problem POVS and asks whether a given graph can be turned into a graph of a specific graph class Π using at most 𝑘 vertex splits. For graph classes Π that can be dfined in monadic second-order graph logic (MSO2), we show that the problem Π-VS can be expressed as an MSO2 formula, resulting in an FPT algorithm for Π-VS parameterized by 𝑘 if Π additionally has bounded treewidth. We obtain the same result for the problem variant using vertex explosions. [2] R. Ahmed, S.G. Kobourov, M. Kryven, An FPT algorithm for bipartite vertex splitting, in: P. Angelini, R. von Hanxleden (Eds.), Graph Drawing and Network Visualization -30th International Symposium, GD 2022, in: Lecture Notes in Computer Science, vol.13764, Springer, 2022, pp.261--268. KW - Vertex splitting KW - Pathwidth 1 KW - 2-layer drawing Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19195 SN - 1879-2294 VL - 2024 IS - 1021 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Łatuszyński, Krzysztof A1 - Rudolf, Daniel T1 - Convergence of hybrid slice sampling via spectral gap JF - Advances in Applied Probability N2 - It is known that the simple slice sampler has robust convergence properties; however, the class of problems where it can be implemented is limited. In contrast, we consider hybrid slice samplers which are easily implementable and where another Markov chain approximately samples the uniform distribution on each slice. Under appropriate assumptions on the Markov chain on the slice, we give a lower bound and an upper bound of the spectral gap of the hybrid slice sampler in terms of the spectral gap of the simple slice sampler. An immediate consequence of this is that the spectral gap and geometric ergodicity of the hybrid slice sampler can be concluded from the spectral gap and geometric ergodicity of the simple version, which is very well understood. These results indicate that robustness properties of the simple slice sampler are inherited by (appropriately designed) easily implementable hybrid versions. We apply the developed theory and analyze a number of specific algorithms, such as the stepping-out shrinkage slice sampling, hit-and-run slice sampling on a class of multivariate targets, and an easily implementable combination of both procedures on multidimensional bimodal densities. KW - Slice sampler KW - spectral gap KW - geometric ergodicity Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19264 SN - 1475-6064 VL - 56 (2024) IS - 4 SP - 1440 EP - 1466 PB - Cambridge University Press CY - Cambridge ER - TY - JOUR A1 - Hofstadler, Julian T1 - Optimal convergence rates of MCMC integration for functions with unbounded second moment JF - Journal of Applied Probability N2 - We study the Markov chain Monte Carlo estimator for numerical integration for func- tions that do not need to be square integrable with respect to the invariant distribution. For chains with a spectral gap we show that the absolute mean error for L^p functions, with p ∈ (1, 2), decreases like n^(1/p)−1 , which is known to be the optimal rate. This improves currently known results where an additional parameter δ > 0 appears and the convergence is of order n^((1+δ)/p)−1 . KW - Markov chain KW - Monte Carlo KW - spectral gap KW - absolute mean error Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19310 VL - 62 (2025) IS - 3 SP - 1069 EP - 1075 PB - Cambridge University Press CY - Cambridge ER - TY - JOUR A1 - Stocker, Armin A1 - Alshawish, Ali A1 - Bor, Martin A1 - Vidler, John A1 - Gouglidis, Antonios A1 - Scott, Andrew A1 - Marnerides, Angelos A1 - De Meer, Hermann A1 - Hutchison, David T1 - An ICT architecture for enabling ancillary services in Distributed Renewable Energy Sources based on the SGAM framework JF - Energy Informatics (2520-8942) N2 - Smart Grids are electrical grids that require a decentralised way of controlling electric power conditioning and thereby control the production and distribution of energy. Yet, the integration of Distributed Renewable Energy Sources (DRESs) in the Smart Grid introduces new challenges with regards to electrical grid balancing and storing of electrical energy, as well as additional monetary costs. Furthermore, the future smart grid also has to take over the provision of Ancillary Services (ASs). In this paper, a distributed ICT infrastructure to solve such challenges, specifically related to ASs in future Smart Grids, is described. The proposed infrastructure is developed on the basis of the Smart Grid Architecture Model (SGAM) framework, which is defined by the European Commission in Smart Grid Mandate M/490. A testbed that provides a flexible, secure, and low-cost version of this architecture, illustrating the separation of systems and responsibilities, and supporting both emulated DRESs and real hardware has been developed. The resulting system supports the integration of a variety of DRESs with a secure two-way communication channel between the monitoring and controlling components. It assists in the analysis of various inter-operabilities and in the verification of eventual system designs. To validate the system design, the mapping of the proposed architecture to the testbed is presented. Further work will help improve the architecture in two directions; first, by investigating specific-purpose use cases, instantiated using this more generic framework; and second, by investigating the effects a realistic number and variety of connected devices within different grid configurations has on the testbed infrastructure. KW - Ancillary services KW - SGAM KW - DRES KW - Smart Grid KW - Engineering KW - Information and Computing Sciences Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:101:1-2022071721175548518669 SN - 2520-8942 VL - 2022 IS - 5 PB - Springer International Publishing CY - Berlin ER - TY - THES A1 - Danner, Julian T1 - SAT Solving Using XOR-OR-AND Normal Forms and Cryptographic Fault Attacks N2 - The Boolean satisfiability problem (SAT) lies at the core of computational logic and has found many applications in verification, cryptography, and artificial intelligence. While conflict-driven SAT solvers (CDCL) excel on large industrial instances, they struggle with XOR-rich instances arising frequently in cryptanalysis, due to the inefficiency of CNF encodings of linear constraints. Conversely, algebraic approaches can work with linear XOR constraints naturally but fail to scale to relevant sizes. Bridging these complementary paradigms with a focus on cryptographic problems is at the heart of this thesis. On one hand, this dissertation advances SAT solving by introducing the XOR-OR-AND normal form (XNF) as a generalization of the conjunctive normal form (CNF), where literals are replaced by XOR chains of literals. This allows for a native representation of XOR constraints. We generalize the CDCL architecture to the richer language of XNFs. The underlying reasoning based on the proof system SRES which is shown to be exponentially stronger than classical resolution. An implementation demonstrates competitive performance and often surpasses state-of-the-art algebraic and logic solvers on random and cryptographic benchmarks. Furthermore, we prove that every XNF formula can be converted in polynomial time to a formula in 2-XNF, enabling a graph-based approach similar to 2-SAT. Building on this, we propose advanced in- and pre-processing techniques, and construct a simple DPLL-based solving framework. Our implementation, 2-Xornado, outperforms modern algebraic and logic solving approaches on many random and some structured cryptographic problems. On the other hand, we apply combined algebraic and logical techniques to cryptanalysis of stream ciphers. We introduce a formal guess-and-determine (GD) framework using a logical abstraction of the information flow in the internal state. From an algebraic point of view, we can then find optimal GD attacks utilizing a Gröbner basis. As a case study, we apply this method to aid in the construction of novel fault attacks on the ciphers KCipher-2 and Enocoro-128v2. Using ad hoc methods combining algebraic and logical approaches, we show that both ciphers are vulnerable to active side-channel attacks under rather weak fault models. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19171 ER - TY - THES A1 - Prummer, Michael T1 - Asset Tokenization and Authentication in the Industrial Metaverse N2 - The Industrial Revolution is a crucial development step in human history that started three centuries ago and is still ongoing. It continually influences and shapes the globalized world. Today, industries account for 20% of carbon dioxide emissions worldwide and require more than a third of global energy consumption. Current problems, such as climate change, increasing waste, and pollution, require simultaneous optimization across all industrial domains, infrastructure, and systems as they depend on each other. The global industry faces the immense challenges of providing for a surging world population expected to peak in the mid-2080s with 10.4 billion people, as reported by the United Nations. Hence, industries are expected to become less resource-intensive, sustainable, and more resilient to disrupted supply chains while producing for a growing population for the next decades. The Fourth Industrial Revolution, or Industry 4.0 (I4.0), started around 2010 and is still an ongoing transformation of industrial processes towards digitalization, creating smart factories referring to the digital data integration of the entire manufacturing cycle. I4.0 is incredibly information-intensive and requires immense data to simulate and predict essential operations based on a digital shadow of the factory, a so-called digital twin. The Metaverse is considered a digitalization megatrend merging digital and physical worlds, creating immersive experiences and new opportunities for interaction and innovation across various sectors and industries. The vision of the Metaverse promotes interconnected and interoperable real-time 3D virtual worlds that can be frictionlessly traversed while sustaining ownership of one's assets under a self-sovereign identity in a decentralized environment without platform lock-ins to a specific ecosystem. Therefore, the Metaverse creates an immersive parallel reality with collective virtually shared spaces for entertainment, social interactions, education, and a new working environment. The Industrial Metaverse synthesizes Metaverse concepts with current industrial automation, such as I4.0, to deepen the digital-physical convergence by interconnecting internal and external systems to enable decision-making and predictions based on significantly broader knowledge. An Industrial Metaverse factory is entirely mirrored to integrate digital twins of all types of equipment, assets, and other entities that can communicate vertically and horizontally, as well as the knowledge about relevant external systems and industrial core sectors. Through the comprehensive data integration of the Industrial Metaverse, AI-driven applications can predict future events, reducing system and hardware failures. Furthermore, the interconnected virtual environments create a meta-ecosystem for global collaboration, providing spaces for solving complex problems such as engineering and product design tasks, simulation of product twins, and reduced development time and costs. The connected industrial ecosystems create a token-based digital economy for exchanging data, assets, and services cross-metaverse connecting isolated data silos. Sharing digital twin resources and services with other systems enables new innovative applications and growing ecosystems. The theoretical part of this thesis defines the essential characteristics and key technologies of the Industrial Metaverse to derive a reference architecture for a decentralized system of systems, outlining the fundamental Industrial Metaverse building blocks. Interoperable data exchange, access management, and system communication are critical challenges. Especially interoperability of assets such as 3D files that come in different formats and identities must be ensured to move between virtual environments. The unique fusion of technologies leverages interconnected digital twins in the context of immersion, interaction, and collaboration for secure, autonomous-governed, decentralized industrial applications. Hence, the Industrial Metaverse requires the possibility of exchanging assets, products, and services across all systems in a secure manner. Distributed ledger technology enables tamper-proof transactions of assets and value in a decentralized token economy. Therefore, we investigate the feasibility of current tokenization methods for industrial assets, in particular, Printed Circuit Board (PCB) designs and 3D models. We contribute methods to create unique fingerprints of PCB designs to enable their exchange in the token economy. We investigate how to bind files in different formats and quality representations to the same token. A robust multi-file binding based on the copper layers of a PCB design was achieved by calculating an adaptive perceptual hash of all files. The adaptive perceptual hash was evaluated against numerous tamperings of the routing layout of a PCB, showing decent resistance to layout changes. The resulting adaptive perceptual hash can be used as an additional identification attribute in a tokenized asset. Furthermore, assets must be authenticatable and verifiable by marketplaces, manufacturers, and other participants to create trust in a decentralized environment. While assets can be tampered with to manipulate, for example, cryptographic hashes that link the file to the token, perceptual hashes can compute a perceived or functional similarity of two objects instead of the plain file integrity. Without the possibility of verifying and protecting intellectual property, mass adoption of the Metaverse and Industrial Metaverse is unlikely. Therefore, we contribute to detecting tampering attacks on 3D models by introducing a 3D perceptual hash that is robust to a set of mesh manipulations, enabling the trusted exchange and authentication of 3D data in the Metaverse. KW - 3D Perceptual hash KW - Industrial Metaverse Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19566 ER - TY - THES A1 - Ellinger, Simon T1 - On optimal error rates for strong approximation of stochastic differential equations with irregular drift coefficients N2 - In this dissertation we study strong approximation of stochastic differential equations (SDEs) with irregular drift coefficients at the final time point or globally in time by methods that use only finitely many evaluations of the driving Brownian motion. We show the optimality of well-known methods, such as the Euler-Maruyama scheme or a transformed Milstein scheme, for classes of piecewise Lipschitz continuous, Hölder continuous and Sobolev regular drift coefficients. To do this, we derive the optimal error rates for the different classes of irregular drift coefficients. Furthermore, we show that the solution of an SDE with piecewise Hölder continuous drift coefficient has a regular local density, which is used in the proofs of the lower bounds. KW - Complexity KW - Error rates KW - Stochastic differential equations KW - Non-Lipschitz drift coefficient KW - Strong approximation KW - Lower error bounds Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19634 ER - TY - THES A1 - Henle, Mona T1 - Multi-Leader Congestion Games with an Adversary N2 - In this thesis, we introduced a congestion game with multiple leaders and a single follower (adversary) which is motivated by security applications with congestion effects. Our objective was to understand the result and the impact of selfish acting individuals in these games. In this regard, we analyzed the existence, the computation and the quality of (approximate) pure Nash equilibria. First, we observed that an exact pure Nash equilibrium always exists in the resulting strategic game among the leaders if the resource cost coefficients are identical and the underlying congestion game is a matroid congestion game. If one of these two conditions is not fulfilled, the existence of PNE is not ensured anymore in general. Consequently, we focused on approximate equilibria. For the case of symmetric singleton strategies, one of our main result established that K ≈ 1.1974, the unique solution of a cubic polynomial equation, is the smallest possible factor such that the existence of a K-approximate equilibrium is guaranteed for all instances of the game. To this end, we presented an efficient algorithm which computes a K-approximate PNE. Furthermore, we showed that the factor K is tight by providing an instance where no α-approximate PNE with α < K exists. However, for a specific symmetric singleton instance there might be a better α-approximate PNE, i.e., with α < K. A given instance could even admit an exact PNE. We provided therefore a polynomial time procedure that computes a best approximate PNE of a given instance. In particular, this procedure can verify the existence of an exact PNE in a given instance efficiently and, if it exists, can also determine the corresponding load vector. Finally, for symmetric singleton instances with two resources, we compared the total cost of a best (cheapest) and worst (most expensive) PNE to the total cost of an optimal outcome, termed by the price of stability and the price of anarchy, respectively. In particular, we verified that the PoS and the PoA are 4/3. KW - Congestion Games KW - Game Theory KW - Adversary KW - Spieltheorie Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19683 ER - TY - THES A1 - Schiermeier, Kathrin T1 - Multidimensional Wavelets and Neural Networks N2 - The construction of scaling functions and wavelets in multiple dimensions and for arbitrary scaling matrices is a challenging task entailing some complexities. Existing approaches mainly focus on the two-dimensional case using dyadic or quincunx sampling. This thesis aims to develop a method to construct multidimensional scaling and wavelet filters yielding orthogonal scaling functions and wavelets under the usage of convolutional neural networks. We start by recalling substantial fundamentals of ideals, modules, Fourier analysis, filterbanks and multiresolution analyses, where the mentioned concepts are already considered in an arbitrary dimensional setting to prepare the proof of the main result. There, we show the connection between multivariate scaling functions and multidimensional filters possessing certain properties. This enables us to construct scaling functions and corresponding wavelets by discrete filter design. Exploiting the link between the discrete wavelet decomposition, filterbanks and neural networks, we utilize the latter to do so. Being the main difficulty of this process, we especially focus on the Cohen criterion, which concerns the zeros of the Fourier transform of the scaling filter in modulus representing a multivariate trigonometric polynomial. After transferring the Bernstein inequality for univariate trigonomic polynomials to multiple dimensions, we present a method to derive a finite set of inequality constraints implying that the Cohen criterion holds true for a given multivariate cosine sum. Afterwards, we introduce neural networks and TensorFlow as the main tools to execute the described approach, formulate the described objective as an optimization problem and present some smaller numerical experiments and their results. A second objective of this thesis is the construction of filters possessing a unimodular modulation vector and therefore the ability to be completed to a perfect reconstruction filterbank. Both - the construction and the filterbank completion - can also be considered in a neural network framework as we will detail in the last section of this thesis alongside with the presentation of corresponding numerical experiments. In the context of filterbank completion, a further observation which allows to complete any given interpolatory filter to a perfect reconstruction filterbank in a very intuitive and simple way is presented. Furthermore, we explain that any given unimodular filter can be rendered interpolatory through prefiltering. KW - Wavelets KW - Filterbanks KW - Convolutional Neural Networks Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19742 ER - TY - THES A1 - Wendlinger, Lorenz T1 - Structure-aware Deep Learning N2 - Graph structures permeate the digital landscape in explicit and implicit forms. They connect or construct artifacts by combining semantic and structural information. We also observe them in the systems designed to process this data, in their learning algorithms and the very nature of the tasks they solve. At the same time, machine learning methods are extremely data-hungry, requiring petabytes of data for training. Due to their complexity, graphs remain an under-utilized resource in this regard. Many approaches cannot incorporate them due to being fully structurally unaware or not suited to the specific flavour of graphs encountered in some domains. This disconnect is sub-optimal from an effectiveness and efficiency perspective. We present methods that extend the scope of structure-aware deep learning through structural knowledge integration and enrichment, structural performance prediction, and synergistic transfer learning. Knowledge graphs organize information and make it directly available for querying. They provide a structured inference interface for manual and automated inspection, though they can suffer from data quality issues and require careful schema design. We rephrase the reconciliation of knowledge in knowledge graphs as a link prediction task, making it tractable with adapted graph neural networks, while also benefiting conventional link prediction tasks. We further combine textual semantics and structural expression for legal reference prediction via adapted heterogeneous graph neural networks operating on complex meta-information enriched graphs. Additionally, we explore methods for the integration of intermediary expressions in strongly typed heterogeneous graphs, improving prediction via meta-path-based processing. We also develop methods for automated machine learning workflow analysis and performance prediction. This includes the learning of salient representations for management as well as improvement of workflows through automatic suggestion and refinement of components. These are then extended to the prediction of Neural Architecture Search performance prediction, including adaptation to operation-on-edge spaces. Finally, we investigate the transfer capability of pre-trained attention structures for text-based prediction tasks and find it to be both inferior to directly optimized attention masks as well as highly dependent on inherent domain knowledge. We also show that the exploitation of hierarchical task formulation can improve prediction performance through joint learning in diverse learning domains, including link prediction, performance prediction, and specialized and general argumentation mining. The dissertation contains previously published or submitted texts: Wendlinger, L., Hübscher, G., Ekelhart, A., Granitzer, M. (2022). Reconciliation of Mental Concepts with Graph Neural Networks. In: Strauss, C., Cuzzocrea, A., Kotsis, G., Tjoa, A.M., Khalil, I. (eds): Database and Expert Systems Applications. DEXA 2022. Lecture Notes in Computer Science, vol 13427, p 133-146. Springer, Cham. https://doi.org/10.1007/978-3-031-12426-6_11; Wendlinger, L., Granitzer M. (2024). Informed Heterogeneous Attention Networks for Metapath Based Learning. In: SAC '24: Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing, p 458-465, ACM, New York. https://doi.org/10.1145/3605098.3635890; Wendlinger, L., Nonn, S.A., Al Zubaer, A., Granitzer, M. (2026). The Missing Link: Joint Legal Citation Prediction Using Heterogeneous Graph Enrichment. In: Wrembel, R., Kotsis, G., Tjoa, A.M., Khalil, I. (eds) Database and Expert Systems Applications. DEXA 2025. Lecture Notes in Computer Science, vol 16047, p 197-211. Springer, Cham. https://doi.org/10.1007/978-3-032-02088-8_14; Wendlinger, L., Stier, J., Granitzer, M. (2021). Evofficient: Reproducing a Cartesian Genetic Programming Method. In: Hu, T., Lourenço, N., Medvet, E. (eds) Genetic Programming. EuroGP 2021. Lecture Notes in Computer Science, vol 12691, p 162-178. Springer, Cham. https://doi.org/10.1007/978-3-030-72812-0_11; Wendlinger, L., Berndl, E., Granitzer, M. (2021). Methods for Automatic Machine-Learning Workflow Analysis. In: Dong, Y., Kourtellis, N., Hammer, B., Lozano, J.A. (eds) Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track. ECML PKDD 2021. Lecture Notes in Computer Science, vol 12979, p 52-67. Springer, Cham. https://doi.org/10.1007/978-3-030-86517-7_4; Wendlinger, L., Granitzer, M., Fellicious, C. (2023). Pooling Graph Convolutional Networks for Structural Performance Prediction. In: Nicosia, G., et al. (eds) Machine Learning, Optimization, and Data Science. LOD 2022. Lecture Notes in Computer Science, vol 13811, p 1-16. Springer, Cham. https://doi.org/10.1007/978-3-031-25891-6_1; Wendlinger, L., Braun, C., Zubaer, A., Nonn, S., Großkopf, S., Fellicious, C., Granitzer, M.: On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education, submitted to the proceedings of the International Conference on Machine Learning, Optimization, and Data Science 2025, preprint published: https://doi.org/10.48550/arXiv.2412.15902; Wendlinger, L., Kuhn, R., Mitrovic, J., Granitzer, M. (2025). Joint Learning for Efficient German Argument Mining. In: 2025 IEEE 37th International Conference on Tools with Artificial Intelligence (ICTAI), Athens, Greece, 2025, p 770-777. IEEE, Los Alamitos. https://doi.org/10.1109/ICTAI66417.2025.00111. N2 - Graphenstrukturen durchdringen die digitale Landschaft in expliziten und impliziten Formen. Sie verbinden oder konstruieren Artefakte, indem sie semantische und strukturelle Informationen kombinieren. Wir beobachten sie auch in den Systemen, die zur Verarbeitung dieser Daten entwickelt wurden, in ihren Lernalgorithmen und in der Art der Aufgaben, die sie lösen. Gleichzeitig sind die Methoden des maschinellen Lernens extrem datenhungrig und benötigen Petabytes an Daten für das Training. Aufgrund ihrer Komplexität bleiben Graphen in dieser Hinsicht eine unzureichend genutzte Ressource. Viele Ansätze können sie nicht einbeziehen, weil sie die Struktur der Graphen nicht kennen oder nicht für die spezielle Art von Graphen geeignet sind, die in einigen Bereichen vorkommen. Diese Trennung ist aus Sicht der Effektivität und Effizienz suboptimal. Wir stellen Methoden vor, die den Anwendungsbereich des strukturbewussten Deep Learning durch strukturelle Wissensintegration und -anreicherung, strukturelle Leistungsvorhersage und synergetisches Transferlernen erweitern. Wissensgraphen organisieren Informationen und machen sie direkt für Abfragen verfügbar. Sie bieten eine strukturierte Inferenzschnittstelle für die manuelle und automatische Überprüfung, obwohl sie unter Problemen der Datenqualität leiden können und ein sorgfältiges Schemadesign erfordern. Wir formulieren den Abgleich von Wissen in Wissensgraphen als eine Aufgabe der Kantenvorhersage um, die mit angepassten neuronalen Netzen für Graphen durchführbar ist und auch konventionellen Kantenvorhersageaufgaben zugute kommt. Darüber hinaus kombinieren wir Textsemantik und strukturelle Ausdrücke für die Vorhersage rechtlicher Verweise mit Hilfe angepasster heterogener Graph neuronaler Netze, die auf komplexen, mit Metainformationen angereicherten Graphen arbeiten. Darüber hinaus erforschen wir Methoden zur Integration von intermediären Ausdrücken in stark typisierten heterogenen Graphen und verbessern die Vorhersage durch metapfadbasierte Verarbeitung. Wir entwickeln auch Methoden für die automatische Analyse von Prozessbeschreibungen und Leistungsvorhersagen für maschinelles Lernen. Dies beinhaltet das Lernen von bedeutungsvollen Repräsentationen für das Management sowie die Verbesserung von Prozessbeschreibungen durch automatische Vorschläge und Verfeinerung von Komponenten. Diese Methoden werden dann auf die Leistungsvorhersage der neuronalen Architektursuche ausgeweitet, einschließlich der Anpassung an die Operation-on-Edge-Räume. Schließlich untersuchen wir die Transferfähigkeit von vortrainierten Aufmerksamkeitsstrukturen für textbasierte Vorhersageaufgaben und stellen fest, dass diese sowohl den direkt optimierten Aufmerksamkeitsmasken unterlegen sind als auch in hohem Maße vom inhärenten Domänenwissen abhängen. Wir zeigen auch, dass die Ausnutzung hierarchischer Aufgabenformulierung die Vorhersageleistung durch gemeinsames Lernen in verschiedenen Lernbereichen verbessern kann, einschließlich Kantenvorhersage, Leistungsvorhersage und spezialisierter und allgemeiner Argumentationsanalyse. Die Dissertation beinhaltet bereits veröffentlichte oder zur Veröffentlichung vorgesehene Texte: Wendlinger, L., Hübscher, G., Ekelhart, A., Granitzer, M. (2022). Reconciliation of Mental Concepts with Graph Neural Networks. In: Strauss, C., Cuzzocrea, A., Kotsis, G., Tjoa, A.M., Khalil, I. (Hgg.): Database and Expert Systems Applications. DEXA 2022. Lecture Notes in Computer Science, vol 13427, S. 133-146. Springer, Cham. https://doi.org/10.1007/978-3-031-12426-6_11; Wendlinger, L., Granitzer M. (2024). Informed Heterogeneous Attention Networks for Metapath Based Learning. In: SAC '24: Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing, S. 458-465, ACM, New York. https://doi.org/10.1145/3605098.3635890; Wendlinger, L., Nonn, S.A., Al Zubaer, A., Granitzer, M. (2026). The Missing Link: Joint Legal Citation Prediction Using Heterogeneous Graph Enrichment. In: Wrembel, R., Kotsis, G., Tjoa, A.M., Khalil, I. (Hgg.) Database and Expert Systems Applications. DEXA 2025. Lecture Notes in Computer Science, vol 16047, S. 197-211. Springer, Cham. https://doi.org/10.1007/978-3-032-02088-8_14; Wendlinger, L., Stier, J., Granitzer, M. (2021). Evofficient: Reproducing a Cartesian Genetic Programming Method. In: Hu, T., Lourenço, N., Medvet, E. (Hgg.) Genetic Programming. EuroGP 2021. Lecture Notes in Computer Science, vol 12691, S. 162-178. Springer, Cham. https://doi.org/10.1007/978-3-030-72812-0_11; Wendlinger, L., Berndl, E., Granitzer, M. (2021). Methods for Automatic Machine-Learning Workflow Analysis. In: Dong, Y., Kourtellis, N., Hammer, B., Lozano, J.A. (Hgg.) Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track. ECML PKDD 2021. Lecture Notes in Computer Science, vol 12979, S. 52-67. Springer, Cham. https://doi.org/10.1007/978-3-030-86517-7_4; Wendlinger, L., Granitzer, M., Fellicious, C. (2023). Pooling Graph Convolutional Networks for Structural Performance Prediction. In: Nicosia, G., et al. Machine Learning, Optimization, and Data Science. LOD 2022. Lecture Notes in Computer Science, vol 13811, S. 1-16. Springer, Cham. https://doi.org/10.1007/978-3-031-25891-6_1; Wendlinger, L., Braun, C., Zubaer, A., Nonn, S., Großkopf, S., Fellicious, C., Granitzer, M.: On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education, eingereicht für die Proceedings der International Conference on Machine Learning, Optimization, and Data Science 2025, vorab veröffentlicht: https://doi.org/10.48550/arXiv.2412.15902; Wendlinger, L., Kuhn, R., Mitrovic, J., Granitzer, M. (2025). Joint Learning for Efficient German Argument Mining. In: 2025 IEEE 37th International Conference on Tools with Artificial Intelligence (ICTAI), Athens, Greece, 2025, S. 770-777. IEEE, Los Alamitos. https://doi.org/10.1109/ICTAI66417.2025.00111. KW - graph neural networks KW - knowledge graphs KW - structural knowledge integration KW - structural performance prediction KW - synergistic transfer learning KW - link prediction tasks Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19892 ER - TY - THES A1 - Neuwirth, Daniel T1 - Einbettung und Charakterisierung von aligned bar 1-visibility Graphen und outer fan free Graphen N2 - In dieser Arbeit werden drei verschiedene Klassen von Graphen untersucht. Die Klassen sind die bar (1;1)-visibilty Graphen, die aligned bar 1-visibility Graphen und die outer fan free Graphen. Die Klassen werden durch ihre möglichen Einbettungen charakterisiert. Die Repräsentation der bar (1; j)-visibility Graphen ist, dass jeder Knoten als horizontaler Strich und jede Kante als vertikaler Strich gezeichnet wird. Eine Kante kann einen Knoten genau einmal schneiden und ein Knoten kann j-mal geschnitten werden. Wir erweitern die Ergebnisse von Dean et. al. und geben Beispiele mit einer maximalen Dichte an für bar (1; 2)-visibility, bar (1; 3)-visibility und bar (1; 4)-visibility Graphen und geben einen maximal dünnen Graphen für die Klasse der bar (1;1) visibility Graphen an. Wir zeigen, dass die Klassen der bar (1; j)-visibility Graphen für 1 < j < 1eine unendliche Hierarchie bilden. Abschließend beweisen wir, dass das Erkennungsproblem ob ein Graph eine bar (1;1)-visibility Repräsentation hat, NP-vollständig ist. Die Klasse der aligned bar 1-visibility Graphen (AB1V ) erhält man, indem man die bar (1;1)-visibility Repräsentation um 90 Grad dreht und alle Knoten verlängert, so dass diese alle mit der y-Koordinate 0 starten. Die relative Position bzgl. der x-Koordinate wird mit der t-Ordnung beschrieben und mit der r-Ordnung die relative Position bzgl. der y-Koordinate. Wir erweitern die Erkenntnisse von Felsner und Massow für die Klasse der AB1V Graphen bzgl. ihrer maximalen Dichte, der minimale Grad eines Knotens. Wir führen die Methode Pfadaddition ein, um anhand deren Abschlusseigenschaften zu unterscheiden, ob ein Graph in einer Klasse liegt oder nicht. Diese Methode nutzen wir, um die Beziehung der Klasse der AB1V Graphen mit anderen Klassen zu untersuchen. Für die Klasse der maximalen Graphen geben wir einen dünnen Graphen und eine untere Schranke bzgl. der Dichte an. Wir geben einen Algorithmus an, welcher eine Bucheinbettung aus einer AB1V Einbettung berechnet. Für die Klassen der optimalen AB1V Graphen geben wir einen Einbettungsalgorithmus an. Wir verbessern den Erkennungsalgorithmus von Felsner und Massow, ob ein Graph mit einer gegebenen t-Ordnung eine AB1V Einbettung besitzt. Für die Klasse der distinkt strong AB1V Graphen, Graphen in der jeder Knoten ein unterschiedliche r-Ordnung hat und maximal für die r-Ordnung ist, geben wir einen Algorithmus an, der in O(n6) eine mögliche Einbettung berechnet. Zum Schluss zeigen wir für diese Klasse, dass es exponentiell viele verschiedene Einbettungen gibt. Ein Graph hat eine outer fan free Einbettung, wenn alle Knoten inzident zu einer Fläche sind und keine Kante von zwei Kanten geschnitten wird, die adjazent zu einem Knoten sind. Wir untersuchen diese Klasse zuerst auf die Dichte. Weiter erforschen wir die Beziehung zwischen den Klassen der AB1V , RAC und k-planaren Graphen. Abschließend geben wir eine Reduktion von NAE-3-SAT auf das Erkennungsproblem von outer fan free Graphen an. KW - Graph Drawing Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-19930 ER - TY - THES A1 - Frank, Florian T1 - Integrating physical unclonable functions from novel nanomaterials, circuit elements, and memory technologies into future hardware architectures N2 - Cryptographic keys are fundamental components for ensuring security in digital systems. To ensure reliable key generation and management, various technical concepts have been developed, primarily based on dedicated hardware components such as Trusted Platform Modules (TPMs). However, many modern systems, especially small resource-constrained devices, typically lack hardware support for secure key generation and management. To address these limitations, Physical Unclonable Functions (PUFs) have proven to be an effective solution for key generation, device authentication, and identification tasks. PUFs leverage inherent variations in hardware components to produce unique, device-specific keys. For a well-designed PUF, these keys can be reproduced reliably on the same device but are practically impossible to clone. Various types of PUFs exist, including those that exploit slight delay differences in circuits with symmetric paths. Others rely on physical characteristics of components already present in the computing system, such as SRAM or DRAM. However, many of these constructions rely on technologies that could be replaced by emerging ones in the future. Such a replacement may involve a transition from traditional memory technologies, such as SRAM, DRAM, and flash memory, to emerging Non-Volatile Memories (NVMs), including Ferroelectric RAM (FRAM), Magnetoresistive RAM (MRAM), and Resistive RAM (ReRAM). These new technologies, in turn, necessitate innovative hardware security solutions for generating intrinsic hardware fingerprints, ensuring security for next-generation embedded devices. Furthermore, the integration of nanomaterials, such as carbon nanotubes, into processor architectures and the adoption of reconfigurable hardware platforms like Field-Programmable Gate Arrays (FPGAs) require the development of specifically tailored cybersecurity solutions. This dissertation aims to develop hardware-based security mechanisms for these types of devices by designing new PUF constructions and demonstrating their practical applications. One focus lies on PUFs extracted from nanomaterials and emerging circuit elements, particularly memristive devices and Carbon NanoTube Field-Effect Transistors (CNT-FETs). For memristive devices, which form the basis of ReRAM memory, this work analyzes methods ranging from simple binary quantization to advanced techniques exploiting device-specific response patterns. In the case of CNT-FETs, custom-fabricated wafers are developed to construct PUFs with optimal properties, such as high robustness, uniformity, and entropy, even under varying environmental conditions. These conditions include fluctuations in ambient temperature. Based on an analysis of fundamental system components, this work evaluates the feasibility of deriving PUFs from fully integrated circuits. A specific focus is placed on emerging non-volatile memory technologies, assessing their potential for PUF applications. To achieve PUF behavior in these memory devices, techniques such as intentional timing manipulation, induced bit flips through row hammering, and variations in supply voltage are examined. These resulting bit flips can be exploited as PUF responses. Additionally, transforming raw PUF responses into cryptographically usable keys and integrating specific PUFs into practical applications are core components of this work. The demonstrated practical applications include an innovative architecture for encrypting and binding data to non-volatile memory modules, implemented on Multiprocessor System-on-Chips (MPSoCs) incorporating FPGAs. This architecture enables the storage of confidential data on non-volatile memory while simultaneously using the same module as a PUF, without requiring separate memory partitions solely for the PUF functionality. Finally, practical applications of hardware fingerprints in the automotive sector are demonstrated, including an FPGA-based implementation to maintain security while preserving the temporal determinism of time-critical messages. These goals are met through the use of hardware-implemented cryptographic algorithms coupled with an FPGA-based ring oscillator PUF. To summarize, this work presents new types of PUF implementations, starting with nanomaterials and emerging circuit elements, extending to PUFs derived from integrated circuits, and demonstrates innovative solutions for their integration into MPSoC-based architectures. N2 - Kryptografische Schlüssel bilden die Grundlage nahezu aller Verfahren zur Gewährleistung der IT-Sicherheit in digitalen Systemen. Um deren Generierung und Verwaltung zuverlässig zu ermöglichen, wurden verschiedene technische Konzepte entwickelt, allen voran dedizierte Hardware-Komponenten wie Trusted Platform Modules (TPMs). Ein Nachteil solcher Konzepte ist jedoch, dass diese Module nicht in allen Systemen integrierbar sind, weshalb Mikrocontroller in kleinen eingebetteten Systemen häufig keine Unterstützung für hardwaregestützte Schlüsselverwaltung bieten. Um dennoch eine sichere Kommunikation zu gewährleisten, haben sich kryptografische Schlüssel, die aus sogenannten Physical Unclonable Functions (PUFs) abgeleitet werden, als effektive Lösung bewährt. PUFs nutzen hardwarebedingte physikalische Abweichungen, die häufig durch den Produktionsprozess verursacht werden, um daraus einen unklonbaren, gerätespezifischen kryptografischen Schlüssel zu erzeugen. Ein Beispiel sind verzögerungsbasierte PUFs, die minimale Signalverzögerungen aufgrund geringfügiger Abweichungen in den Leitungslängen sowie weiteren elektrischen Parametern nutzen, um eine unklonbare, gerätegebundene Charakteristik zu extrahieren. Des Weiteren haben sich PUFs, die auf bereits in einem Rechensystem vorhandenen Hardwarekomponenten wie DRAM oder SRAM basieren, als kostengünstige Möglichkeit eines Hardware-Sicherheitsankers erwiesen. Der Großteil der derzeit verfügbaren PUF-Implementierungen basiert jedoch nahezu ausschließlich auf älterer Hardware, wie den oben erwähnten Speichertechnologien. In Zukunft könnten diese jedoch durch neuartige nichtflüchtige Speichertechnologien, insbesondere Ferroelectric RAM (FRAM), Magnetoresistive RAM (MRAM) und Resistive RAM (ReRAM), ersetzt werden. Bei diesen Technologien besteht ebenfalls die Notwendigkeit zur Ableitung von kryptografisch sicheren Schlüsseln, um den Schutz zukünftiger eingebetteter Systeme zu gewährleisten. Weitere zukunftsgerichtete Entwicklungen werden die Integration von Nanomaterialien, beispielsweise in Prozessoren, sowie der vermehrte Einsatz neuer Hardwarearchitekturen, wie etwa solcher auf Basis von Field-Programmable Gate Arrays (FPGAs), umfassen. Diese Dissertation hat sich zum Ziel gesetzt, diese Probleme zu adressieren. Sie umfasst die Entwicklung und Analyse verschiedener Arten neuartiger PUFs sowie deren Integration in praktische Anwendungen. Zunächst wird eine Analyse bestimmter Nanomaterialien durchgeführt, insbesondere die Untersuchung neuartiger, auf Kohlenstoffnanoröhrchen basierender Feldeffekttransistoren. Hierfür wurden speziell gefertigte Siliziumwafer entwickelt, um PUFs mit optimalen Eigenschaften wie hoher Robustheit, Uniqueness und Entropie zu realisieren. Dies soll selbst unter variierenden Umgebungsbedingungen, einschließlich Schwankungen der Umgebungstemperatur, gewährleistet werden. Darüber hinaus wird das Verhalten von memristiven Bauelementen, den Basiselementen von ReRAM Modulen, im Hinblick auf mögliche PUF-Implementierungen untersucht. Dabei werden Lösungen zur binären Klassifikation entwickelt und spezifische Response-Pattern beim Anlegen verschiedener elektrischer Signale untersucht. Im nächsten Schritt wurde die Erzeugung von PUFs in integrierten Schaltkreisen betrachtet, insbesondere in den oben genannten nichtflüchtigen Speichern. Hierzu werden Methoden genutzt, die sich bereits bei älteren Speichermodulen als erfolgreich erwiesen haben. Dazu gehören unter anderem die Variation der Versorgungsspannung, das absichtliche Unterschreiten der Zugriffszeiten sowie das Erzeugen von Bit-Flips mittels Row Hammering. Im letzten Teil dieser Dissertation wird die Integration verschiedener PUFs in praktische Anwendungen untersucht. Zu diesem Zweck wird eine FPGA-basierte Architektur entwickelt, die unter Verwendung von intrinsischen speicherbasierten PUFs das Speichermodul gleichzeitig zum Ablegen vertraulicher Daten nutzt und diese Daten zusätzlich durch einen vom gleichen Modul abgeleiteten Schlüssel an dieses bindet. Dies ist möglich, ohne zusätzlichen Speicherplatz für die PUF-Erzeugung zu reservieren. Ein weiterer praktischer Anwendungsfall im Automotive-Kontext wird demonstriert. Hier wird ebenfalls eine FPGA-basierte Lösung vorgestellt, die Authentizität und Integrität im Fahrzeug gewährleistet und gleichzeitig den zeitlichen Determinismus der Kommunikation im Fahrzeug bewahrt. Dies wird durch den Einsatz hardwaregestützter kryptografischer Algorithmen in Verbindung mit einem FPGA-basierten Ring-Oszillator-PUF erreicht. Zusammenfassend stellt diese Arbeit neuartige PUF-Implementierungen vor, die auf Konstruktionen mit Nanomaterialien und innovativen Schaltungselementen basieren. Aufbauend darauf werden Methoden zur Extraktion von PUFs aus neuartigen nichtflüchtigen Speichertechnologien untersucht. Abschließend werden praxisnahe, innovative Anwendungen auf MPSoC-Plattformen vorgestellt, die den Einsatz von PUFs demonstrieren. KW - Physical Unclonable Functions KW - Hardware Security KW - Nanomaterials KW - Emerging Memory Technologies KW - FPGAs Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-20104 ER - TY - RPRT A1 - Almaini, Amar A1 - Anthuber, Stefan A1 - Egger, Gottfried A1 - Grabner, Daniel A1 - Gutbrod, Amelie A1 - Herburger, Michael A1 - Holzer, Laura A1 - Icyer, Abdurrahman A1 - Katzenbeisser, Stefan A1 - Kraxberger, Manuel A1 - Kufner, Sven A1 - Langner, Karoline A1 - Lill, Bjarne A1 - Mexis, Nico A1 - Pichler, Julia A1 - Plasch, Michael A1 - Sauerwein, Clemens A1 - Schramm, Martin A1 - Szilagyi, Daniel A1 - Wagner, Carina A1 - Zeisler, Alexander T1 - Cyber-Security und Resilienz in Supply Chains mit Fokus auf KMU N2 - Dieser Best Practice Guide zeigt, wie kleine und mittlere Unternehmen (KMU) ihre Cyber-Resilienz umfassend stärken können, von der technischen Basis über Lieferketten und Unternehmenskultur bis hin zu Notfallmanagement und OT-Security. Da Cyberangriffe zunehmend komplexer werden und menschliches Verhalten weiterhin in über 80 % der Vorfälle eine entscheidende Rolle spielt, reicht technische Absicherung allein nicht aus. Entscheidend ist ein integrierter Ansatz, der Mindset (sicherheitsbewusste Haltung), Skillset (praktisches Wissen und regelmäßige Schulungen) und Toolset (adäquate technische Lösungen) miteinander verbindet. Der Cyber-Security Grundschutz vermittelt KMU praxisnahe Schritte zur Identifikation des IST-Zustands, zur Priorisierung von Schutzmaßnahmen und zur Einführung eines kontinuierlichen Verbesserungsprozesses nach dem PDCA-Modell. Das Supply Chain Cyber-Security Handbuch verdeutlicht, wie digital vernetzte Lieferketten zu kritischen Angriffspunkten werden können und unterstützt Unternehmen dabei, relevante Partner zu identifizieren, zu klassifizieren und risikobasierte Maßnahmen zu implementieren. Das Awareness- & Kultur-Handbuch zeigt, wie eine „Security-First“-Kultur entsteht, die Cybersicherheit als Teamaufgabe begreift und über Zero-Trust-Prinzipien, klare Verantwortlichkeiten und moderne Lernformate wie Serious Games nachhaltig verankert. Das Cyber-Notfallkonzept bietet KMU einen strukturierten Leitfaden zur Vorbereitung, Reaktion und Wiederherstellung bei Sicherheitsvorfällen - inklusive Checklisten, Rollenmodellen und Incident-Response-Plänen, um Ausfallzeiten zu minimieren und handlungsfähig zu bleiben. Ergänzend vermittelt das OT-Security Handbuch die Besonderheiten industrieller Systeme und zeigt, wie KMU ihre Produktionsumgebungen schützen können - von der Bewertung kritischer Anlagen über sichere Konfigurationen bis zur schrittweisen Umsetzung praxistauglicher OT-Security-Maßnahmen. Gemeinsam bilden die fünf Handbücher ein ganzheitliches Rahmenwerk, das KMU befähigt, Cybersicherheit als festen Bestandteil des Arbeitsalltags zu verankern, Risiken entlang der gesamten Wertschöpfungskette zu reduzieren und die eigene Widerstandsfähigkeit gegenüber Cyberbedrohungen systematisch zu erhöhen. T2 - Cyber-Security and Resilience in Supply Chains With a Focus on SMEs KW - Cybersicherheit KW - Cyber Security KW - Kleine und Mittlere Unternehmen (KMU) KW - Small and Medium-sized Enterprises (SME) Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-20549 ER -