@inproceedings{ParraRodriguezPosegga2018, author = {Parra Rodriguez, Juan D. and Posegga, Joachim}, title = {RAPID: Resource and API-Based Detection Against In-Browser Miners}, series = {Proceedings of the 34th Annual Computer Security Applications Conference}, booktitle = {Proceedings of the 34th Annual Computer Security Applications Conference}, publisher = {ACM}, address = {New York, NY, USA}, isbn = {978-1-4503-6569-7}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus4-6550}, pages = {[14] Seiten}, year = {2018}, abstract = {Direct access to the system's resources such as the GPU, persistent storage and networking has enabled in-browser crypto-mining. Thus, there has been a massive response by rogue actors who abuse browsers for mining without the user's consent. This trend has grown steadily for the last months until this practice, i.e., CryptoJacking, has been acknowledged as the number one security threat by several antivirus companies. Considering this, and the fact that these attacks do not behave as JavaScript malware or other Web attacks, we propose and evaluate several approaches to detect in-browser mining. To this end, we collect information from the top 330.500 Alexa sites. Mainly, we used real-life browsers to visit sites while monitoring resource-related API calls and the browser's resource consumption, e.g., CPU. Our detection mechanisms are based on dynamic monitoring, so they are resistant to JavaScript obfuscation. Furthermore, our detection techniques can generalize well and classify previously unseen samples with up to 99.99\\% precision and recall for the benign class and up to 96\\% precision and recall for the mining class. These results demonstrate the applicability of detection mechanisms as a server-side approach, e.g., to support the enhancement of existing blacklists. Last but not least, we evaluated the feasibility of deploying prototypical implementations of some detection mechanisms directly on the browser. Specifically, we measured the impact of in-browser API monitoring on page-loading time and performed micro-benchmarks for the execution of some classifiers directly within the browser. In this regard, we ascertain that, even though there are engineering challenges to overcome, it is feasible and beneficial for users to bring the mining detection to the browser.}, language = {en} } @inproceedings{ParraRodriguezSchrecklingPosegga2017, author = {Parra Rodriguez, Juan D. and Schreckling, Daniel and Posegga, Joachim}, title = {Addressing Data-Centric Security Requirements for IoT-Based Systems}, series = {2016 International Workshop on Secure Internet of Things (SIoT)}, booktitle = {2016 International Workshop on Secure Internet of Things (SIoT)}, publisher = {IEEE Xplore}, address = {Heraklion, Greece}, isbn = {978-1-5090-5091-8}, doi = {10.1109/SIoT.2016.007}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus4-6546}, pages = {[10] Seiten}, year = {2017}, abstract = {Allowing users to control access to their data is paramount for the success of the Internet of Things; therefore, it is imperative to ensure it, even when data has left the users' control, e.g. shared with cloud infrastructure. Consequently, we propose several state of the art mechanisms from the security and privacy research fields to cope with this requirement. To illustrate how each mechanism can be applied, we derive a data-centric architecture providing access control and privacy guaranties for the users of IoT-based applications. Moreover, we discuss the limitations and challenges related to applying the selected mechanisms to ensure access control remotely. Also, we validate our architecture by showing how it empowers users to control access to their health data in a quantified self use case.}, language = {en} } @inproceedings{ParraRodriguezPosegga2018, author = {Parra Rodriguez, Juan D. and Posegga, Joachim}, title = {Local Storage on Steroids: Abusing Web Browsers for Hidden Content Storage and Distribution}, series = {International Conference on Security and Privacy in Communication Systems}, booktitle = {International Conference on Security and Privacy in Communication Systems}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-01704-0}, doi = {10.1007/978-3-030-01704-0_19}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus4-6572}, pages = {20 Seiten}, year = {2018}, abstract = {Analysing security assumptions taken for the WebRTC and postMessage APIs led us to find a novel attack abusing the browsers' persistent storage capabilities. The presented attack can be executed without the website's visitor knowledge, and it requires neither browser vulnerabilities nor additional software on the browser's side. To exemplify this, we study how can an attacker use browsers to create a network for persistent storage and distribution of arbitrary data. In our proof of concept, the total storage of the network, and therefore the space used within each browser, grows linearly with the number of origins delivering the malicious JavaScript code. Further, data transfers between browsers are not restricted by the Same Origin Policy, which allows for a unified cross-origin browser network, regardless of the origin from which the script executing the functionality is loaded from. In the course of our work, we assess the feasibility of a real-life deployment of the network by running experiments using Linux containers and browser automation tools. Moreover, we show how security mechanisms against third-party tracking, cross-site scripting and click-jacking can diminish the attack's impact, or even prevent it.}, language = {en} } @inproceedings{ParraRodriguezPosegga2017, author = {Parra Rodriguez, Juan D. and Posegga, Joachim}, title = {CSP \& Co. Can Save Us from a Rogue Cross-Origin Storage Browser Network! But for How Long?}, series = {Proceedings of the Eighth ACM Conference on Data and Application Security and Privacy}, booktitle = {Proceedings of the Eighth ACM Conference on Data and Application Security and Privacy}, publisher = {ACM}, address = {New York, NY, USA}, isbn = {978-1-4503-5632-9}, doi = {10.1145/3176258.3176951}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus4-6561}, pages = {3 Seiten}, year = {2017}, abstract = {We introduce a new browser abuse scenario where an attacker uses local storage capabilities without the website's visitor knowledge to create a network of browsers for persistent storage and distribution of arbitrary data. We describe how security-aware users can use mechanisms such as the Content Security Policy (CSP), sandboxing, and third-party tracking protection, i.e., CSP \& Company, to limit the network's effectiveness. From another point of view, we also show that the upcoming Suborigin standard can inadvertently thwart existing countermeasures, if it is adopted.}, language = {en} } @phdthesis{Ganser2019, author = {Ganser, Stefan}, title = {Iterative Schedule Optimization for Parallelization in the Polyhedron Model}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus4-7936}, school = {Universit{\"a}t Passau}, pages = {xvii, 176 Seiten}, year = {2019}, abstract = {In high-performance computing, one primary objective is to exploit the performance that the given target hardware can deliver to the fullest. Compilers that have the ability to automatically optimize programs for a specific target hardware can be highly useful in this context. Iterative (or search-based) compilation requires little or no prior knowledge and can adapt more easily to concrete programs and target hardware than static cost models and heuristics. Thereby, iterative compilation helps in situations in which static heuristics do not reflect the combination of input program and target hardware well. Moreover, iterative compilation may enable the derivation of more accurate cost models and heuristics for optimizing compilers. In this context, the polyhedron model is of help as it provides not only a mathematical representation of programs but, more importantly, a uniform representation of complex sequences of program transformations by schedule functions. The latter facilitates the systematic exploration of the set of legal transformations of a given program. Early approaches to purely iterative schedule optimization in the polyhedron model do not limit their search to schedules that preserve program semantics and, thereby, suffer from the need to explore numbers of illegal schedules. More recent research ensures the legality of program transformations but presumes a sequential rather than a parallel execution of the transformed program. Other approaches do not perform a purely iterative optimization. We propose an approach to iterative schedule optimization for parallelization and tiling in the polyhedron model. Our approach targets loop programs that profit from data locality optimization and coarse-grained loop parallelization. The schedule search space can be explored either randomly or by means of a genetic algorithm. To determine a schedule's profitability, we rely primarily on measuring the transformed code's execution time. While benchmarking is accurate, it increases the time and resource consumption of program optimization tremendously and can even make it impractical. We address this limitation by proposing to learn surrogate models from schedules generated and evaluated in previous runs of the iterative optimization and to replace benchmarking by performance prediction to the extent possible. Our evaluation on the PolyBench 4.1 benchmark set reveals that, in a given setting, iterative schedule optimization yields significantly higher speedups in the execution of the program to be optimized. Surrogate performance models learned from training data that was generated during previous iterative optimizations can reduce the benchmarking effort without strongly impairing the optimization result. A prerequisite for this approach is a sufficient similarity between the training programs and the program to be optimized.}, subject = {Parallelrechner}, language = {en} } @phdthesis{Hatzesberger2020, author = {Hatzesberger, Simon}, title = {Strongly Asymptotically Optimal Methods for the Pathwise Global Approximation of Stochastic Differential Equations with Coefficients of Super-linear Growth}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus4-8100}, school = {Universit{\"a}t Passau}, pages = {ii, 116 Seiten}, year = {2020}, abstract = {Our subject of study is strong approximation of stochastic differential equations (SDEs) with respect to the supremum and the L_p error criteria, and we seek approximations that are strongly asymptotically optimal in specific classes of approximations. For the supremum error, we prove strong asymptotic optimality for specific tamed Euler schemes relating to certain adaptive and to equidistant time discretizations. For the L_p error, we prove strong asymptotic optimality for specific tamed Milstein schemes relating to certain adaptive and to equidistant time discretizations. To illustrate our findings, we numerically analyze the SDE associated with the Heston-3/2-model originating from mathematical finance.}, subject = {Stochastische Differentialgleichung}, language = {en} } @phdthesis{Stahlbauer2019, author = {Stahlbauer, Andreas}, title = {Abstract Transducers for Software Analysis and Verification}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus4-8468}, school = {Universit{\"a}t Passau}, pages = {xv, 187 Seiten}, year = {2019}, abstract = {Whenever software faults can endanger human life, property, or the environment, the absence of faults must be ensured with utmost care and the best technologies available. Evidence is needed showing that all requirements are satisfied and that the risk of faults is reduced. One technique to conduct such a verification task—composed of the software to verify, the specification to check, and a model of the environment—is software model checking. To conduct a verification task with a model checker, different models of the task are constructed. We distinguish between two types of task models: syntactic task models and semantic task models, which define the respective syntactic structure (control flow) and semantic structure (state transitions, invariants) of the verification task. When constructing such models, we can observe that similar structures and substructures reappear within and among different verification tasks. For example, the same assertions to check can appear in different functions, or the same predicate can be part of different invariants to describe sets of program states. Similarities that appear during the model construction process can be the result of solving similar reasoning problems, often solved using computationally expensive procedures (as typical for model checking), over and over again. Not reusing results of solving similar problems, not having a means for conducting repeated efforts automatically, or not trying to reduce the number of similar reasoning efforts, is a waste of precious resources. To address these problems, we present a common conceptual and technical foundation for sharing syntactic and semantic task artifacts for reuse, within and among verification runs. Both the syntactic construction of a verification task and the construction of its semantic model—which describes all possible behaviors and states—are covered. We study how commonalities and regularities in the task models can be taken into account to facilitate the process of sharing task artifacts for reuse, and to make the overall verification process more efficient and effective. We introduce abstract transducers as the theoretical foundation of this thesis: a type of finite-state transducers with an inherent notion of abstraction for states, the input alphabet, and its output alphabet. Abstracting these transducers allows us to widen both the set of input words for that they produce output and the sets of output words. Abstract transducers are instantiated as task artifact transducers to map from program structures to task artifacts to share. We show that the notion of abstraction provides a means for increasing the scope for that task artifacts are shared for reuse. We present two instances of task artifact transducers: Yarn transducers and precision transducers. We use Yarn transducers for providing code to weave into the control-flow structure of a computer program, and present the Loom analysis as a means for orchestrating the weaving process. Precision transducers provide a means for sharing abstraction precisions for reuse, thus aid in defining the level of abstraction of a semantic task model. For both types of transducers, we provide empirical evidence on their practical applicability, for example, to verify Linux kernel modules, and show that they can help in increasing the verification performance.}, subject = {Transduktor}, language = {en} } @phdthesis{Planche2020, author = {Planche, Benjamin}, title = {Bridging the Realism Gap for CAD-Based Visual Recognition}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus4-8361}, school = {Universit{\"a}t Passau}, pages = {xx, 152}, year = {2020}, abstract = {Computer vision aims at developing algorithms to extract high-level information from images and videos. In the industry, for instance, such algorithms are applied to guide manufacturing robots, to visually monitor plants, or to assist human operators in recognizing specific components. Recent progress in computer vision has been dominated by deep artificial neural network, i.e., machine learning methods simulating the way that information flows in our biological brains, and the way that our neural networks adapt and learn from experience. For these methods to learn how to accurately perform complex visual tasks, large amounts of annotated images are needed. Collecting and labeling such domain-relevant training datasets is, however, a tedious—sometimes impossible—task. Therefore, it has become common practice to leverage pre-available three-dimensional (3D) models instead, to generate synthetic images for the recognition algorithms to be trained on. However, methods optimized over synthetic data usually suffer a significant performance drop when applied to real target images. This is due to the realism gap, i.e., the discrepancies between synthetic and real images (in terms of noise, clutter, etc.). In my work, three main directions were explored to bridge this gap. First, an innovative end-to-end framework is proposed to render realistic depth images from 3D models, as a growing number of solutions (especially in the industry) are utilizing low-cost depth cameras (e.g., Microsoft Kinect and Intel RealSense) for recognition tasks. Based on a thorough study of these devices and the different types of noise impairing them, the proposed framework simulates their inner mechanisms, comprehensively modeling vital factors such as sensor noise, material reflectance, surface geometry, etc. Able to simulate a wide panel of depth sensors and to quickly generate large datasets, this framework is used to train algorithms for various recognition tasks, consistently and significantly enhancing their performance compared to other state-of-the-art simulation tools. In some cases, however, relevant 2D or 3D object representations to generate synthetic samples are not available. Considering this different case of data scarcity, a solution is then proposed to incrementally build a representation of visual scenes from partial observations. Provided observations are localized from one to another based on their content and registered in a global memory with spatial properties. Simultaneously, this memory can be queried to render novel views of the scene. Furthermore, unobserved regions can be hallucinated in memory, in consistence with previous observations, hallucinations, and global priors. The efficacy of the proposed mnemonic and generative system, trainable end-to-end, is demonstrated on various 2D and 3D use-cases. Finally, an advanced convolutional neural network pipeline is introduced, tackling the realism gap from a novel angle. While most methods addressing this problem focus on bringing synthetic samples—or the knowledge acquired from them—closer to the real target domain, the proposed solution performs the opposite process, mapping unseen target images into controlled synthetic domains. The pre-processed samples can then be handed to downstream recognition methods, themselves purely trained on similar synthetic data, to greatly improve their accuracy. For each approach, a variety of qualitative and quantitative studies are detailed, providing successful comparisons to state-of-the-art methods. By proposing solutions to bridge the realism gap from either side, as well as a pipeline to improve the acquisition and generation of new visual content, this thesis provides a unique perspective on the challenges of data scarcity when building robust recognition systems.}, language = {en} } @phdthesis{Keren2020, author = {Keren, Gil}, title = {Neural Network Supervision: Notes on Loss Functions, Labels and Confidence Estimation}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus4-8223}, school = {Universit{\"a}t Passau}, pages = {ix, 98 Seiten}, year = {2020}, abstract = {We consider a number of enhancements to the standard neural network training paradigm. First, we show that carefully designed parameter update rules may replace the need for a loss function and its gradient. We introduce a parameter update rule that generalises the standard cross-entropy gradient, and allows directly controlling the relative effect of easy and hard examples on the training process. We show that the proposed update rule cannot be derived by using a loss function and yields better classification accuracy compared to training with the standard cross-entropy loss. In addition, we study the effect of the loss function choice on the learnt representations. We introduce the Single Logit Classification (SLC) task: classifying whether a given class is the correct class for a given example, in a computationally efficient manner, based on the appropriate class logit alone. A natural principle is proposed, the Principle of Logit Separation (PoLS), as a guideline for choosing and designing loss functions suitable for the SLC task. We mathematically analyse the alignment of eleven existing and novel loss functions with this principle. Experiment results show that using loss functions that are aligned with this principle results in a representation in the logits layer in which each logit is more informative of its class correctness, leading to a considerably better SLC accuracy. Further, we attempt to alleviate the dependency of standard neural network models on large amounts of quality labels. The task of weakly supervised one-shot detection is considered, in which at training time the model is trained without any localisation labels, and at test time it needs to identify and localise instances of unseen classes. We propose the attention similarity networks (ASN) for this task. ASN use a Siamese neural network to compute a similarity score between an exemplar and different locations in a target example. Then, an attention mechanism performs localisation by learning to attend to the correct locations. The ASN model outperforms the relevant baselines for weakly supervised one-shot detection tasks in the audio and computer vision domains. Finally, we consider the problem of quantifying prediction confidence in the regression setting. We propose two novel algorithms for emitting calibrated prediction intervals for neural network regressors, at any given confidence level. The two algorithms require binning of the output space and training the neural network regressor as a classifier. Then, the calibration algorithms choose the intervals in the output space, making sure they contain the amount of posterior probability mass that results in the desired confidence level.}, subject = {Neuronales Netz}, language = {en} } @phdthesis{Koop2021, author = {Koop, Martin}, title = {Preventing the Leakage of Privacy Sensitive User Data on the Web}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus4-8717}, school = {Universit{\"a}t Passau}, pages = {137 Seiten}, year = {2021}, abstract = {Das Aufzeichnen der Internetaktivit{\"a}t ist mit der Verkn{\"u}pfung pers{\"o}nlicher Daten zu einer Schl{\"u}sselressource f{\"u}r viele kostenpflichtige und kostenfreie Dienste im Web geworden. Diese Dienste sind zum einen Webanwendungen, wie beispielsweise die von Google bereitgestellten Karten/Navigation oder Websuche, die t{\"a}glich kostenlos verwendet werden. Zum anderen sind es alle Webseiten, die meist kostenlos Nachrichten oder allgemeine Informationen zu verschiedenen Themen bereitstellen. Durch das Aufrufen und die Nutzung dieser Webdienste werden alle Informationen, die im Webdienst verarbeitet werden, an den Dienstanbieter weitergeben. Dies umfasst nicht nur die im Benutzerkonto des Webdienstes gespeicherte Profildaten wie Name oder Adresse, sondern auch die Aktivit{\"a}t mit dem Webdienst wie das anklicken von Links oder die Verweildauer. Dar{\"u}ber hinaus gibt es jedoch auch unz{\"a}hlige Drittparteien, welche zumeist im Hintergrund in die Webdienste eingebunden sind und das Benutzerverhalten der kompletten Webaktivit{\"a}t - Webseiten {\"u}bergreifend - mitspeichern sowie auswerten. Der Einsatz verschiedener, in der Regel f{\"u}r den Benutzer verborgener Techniken, dient dazu das Online-Verhalten der Benutzer genau zu verfolgen und viele sensible Daten zu sammeln. Dieses Verhalten wird als Web-Tracking bezeichnet und wird haupts{\"a}chlich von Werbeunternehmen genutzt. Die gesammelten Daten sind oft personenbezogen und eine wertvolle Ressourcen der Unternehmen, um Beispielsweise passend zum Benutzerprofil personalisierte Werbung schalten zu k{\"o}nnen. Mit der Nutzung dieser personenbezogenen Daten entstehen aber auch weitreichendere Auswirkungen, welche sich unter anderem in Preisanpassungen f{\"u}r Benutzer mit speziellen Profilattributen, wie der Nutzung von teuren Endger{\"a}ten, widerspiegeln. Ziel dieser Arbeit ist es die Privatsph{\"a}re der Nutzer im Internet zu steigern und die Nutzerverfolgung von Web-Tracking signifikant zu reduzieren. Dabei stellen sich vier Herausforderungen, die jeweils einen Forschungsschwerpunkt dieser Arbeit bilden: (1) Systematische Analyse und Einordnung eingesetzter Tracking-Techniken, (2) Untersuchung vorhandener Schutzmechanismen und deren Schwachstellen,(3) Konzeption einer Referenzarchitektur zum Schutz vor Web-Tracking und (4) Entwurf einer automatisierten Testumgebungen unter Realbedingungen, um die Reduzierung von Web-Tracking in den entwickelten Schutzmaßnahmen zu untersuchen. Jeder dieser Forschungsschwerpunkte stellt neue Beitr{\"a}ge bereit, um einheitlich das {\"u}bergeordnete Ziel zu erreichen: der Entwicklung von Schutzmaßnahmen gegen die Preisgabe sensibler Benutzerdaten im Internet. Der erste wissenschaftliche Beitrag dieser Dissertation ist eine umfassende Evaluation eingesetzter Web-Tracking Techniken und Methoden, sowie deren Gefahren, Risiken und Implikationen f{\"u}r die Privatsph{\"a}re der Internetnutzer. Die Evaluation beinhaltet zus{\"a}tzlich die Untersuchung vorhandener Tracking-Schutzmechanismen und deren Schwachstellen. Die gewonnenen Erkenntnisse sind maßgeblich f{\"u}r die in dieser Arbeit neu entwickelten Ans{\"a}tze und verbessern den bisherigen nicht hinreichend gew{\"a}hrleisteten Schutz vor Web-Tracking. Der zweite wissenschaftliche Beitrag ist die Entwicklung einer robusten Klassifizierung von Web-Tracking, der Entwurf einer effizienten Architektur zur Langzeituntersuchung von Web-Tracking sowie einer interaktiven Visualisierung des Auftreten von Web-Tracking im Internet. Dabei basiert der neue Klassifizierungsansatz, um Tracking zu identifizieren, auf der Entropie Messung des Informationsgehalts von Cookies. Die Resultate der Web-Tracking Langzeitstudien sind unter anderem 1.209 identifizierte Tracking-Domains auf den meistbesuchten Webseiten in Deutschland. Hierbei wurden innerhalb der Top 25 Webseiten im Durchschnitt 45 Tracking-Elemente pro Webseite gefunden. Der Tracker mit dem h{\"o}chsten Potenzial zum Erstellen eines Benutzerprofils war doubleclick.com, da er 90\% der Webseiten {\"u}berwacht. Die Auswertung des untersuchten Tracking-Netzwerks ergab weiterhin einen detaillierten Einblick in die Tracking-Technik mithilfe von Weiterleitungslinks. Dabei haben wir 1,2 Millionen HTTP-Traces von monatelangen Crawls der 50.000 international meistbesuchten Webseiten analysiert. Die Ergebnisse zeigen, dass 11,6\% dieser Webseiten HTTP-Redirects, verborgen in Webseiten-Links, zum Tracken verwenden. Dies wird eingesetzt, um den Webseitenverlauf des Benutzers nach dem Klick durch eine Kette von (Tracking-)Servern umzuleiten, welche in der Regel nicht sichtbar sind, bevor das beabsichtigte Link-Ziel geladen wird. In diesem Szenario erfasst der Tracker wertvolle Verbindungs-Metadaten zu Inhalt, Thema oder Benutzerinteressen der Website. Die Visualisierung des Tracking {\"O}kosystem stellen wir in einem interaktiven Open-Source Web-Tool bereit. Der dritte wissenschaftliche Beitrag dieser Dissertation ist die Konzeption von zwei neuartigen Schutzmechanismen gegen Web-Tracking und der Aufbau einer automatisierten Simulationsumgebung unter Realbedingungen, um die Effektivit{\"a}t der Umsetzungen zu verifizieren. Der Fokus liegt auf den beiden meist verwendeten Tracking-Verfahren: Cookies (hierbei wird eine eindeutigen ID auf dem Ger{\"a}t des Benutzers gespeichert), sowie Browser-Fingerprinting. Letzteres beschreibt eine Methode zum Sammeln einer Vielzahl an Ger{\"a}teeigenschaften, um den Benutzer eindeutig zu (re- )identifizieren, ohne eine eindeutige ID auf dem Ger{\"a}t zu speichern. Um die Effektivit{\"a}t der in dieser Arbeit entwickelten Schutzmechanismen vor Web-Tracking zu untersuchen, implementierten und evaluierten wir die Schutzkonzepte direkt im Chromium Browser. Das Ergebnis zeigt eine erfolgreiche Reduzierung von Web-Tracking um 44\%. Zus{\"a}tzlich verbessert das in dieser Arbeit entwickelte Konzept "Site Isolation" den Datenschutz des privaten Browsing-Modus, erm{\"o}glicht das Setzen eines manuellen Speicher-Zeitlimits von Cookies und sch{\"u}tzt den Browser gegen verschiedene Bedrohungen wie CSRF (Cross-Site Request Forgery) oder CORS (Cross-Origin Ressource Sharing). Site Isolation speichert dabei den Status der lokalen Website in separaten Containern und kann dadurch diverse Tracking-Methoden wie Cookies, lokalStorage oder redirect tracking verhindern. Bei der Auswertung von 1,6 Millionen Webseiten haben wir gezeigt, dass der Tracker doubleclick.com das h{\"o}chste Potenzial besitzt, den Nutzer zu verfolgen und auf 25\% der 40.000 international meistbesuchten Webseiten vertreten ist. Schließlich demonstrieren wir in unserem erweiterten Chromium-Browser einen robusten Browser-Fingerprinting-Schutz. Der Test unseres Prototyps mittels 70.000 Browsersitzungen zeigt, dass unser Browser den Nutzer vor sogenanntem Browser-Fingerprinting Tracking sch{\"u}tzt. Im Vergleich zu f{\"u}nf anderen Browser-Fingerprint-Tools erzielte unser Prototyp die besten Ergebnisse und ist der erste Schutzmechanismus gegen Flash sowie Canvas Fingerprinting.}, subject = {Datenschutz}, language = {en} } @phdthesis{Kasinathan2021, author = {Kasinathan, Prabhakaran}, title = {Workflow-aware access control for the Internet of Things}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus4-8915}, school = {Universit{\"a}t Passau}, pages = {xxiii, 214 Seiten}, year = {2021}, abstract = {IoT is defined as a paradigm where "things" have sensing, actuating, communicating, and self-configuring abilities, and are connected to each other and to the Internet. Recent advancements in the manufacturing industry have helped to produce embedded devices with various sensors and actuators in mass numbers at a reduced cost. As part of the IoT revolution, everyday devices such as television, refrigerator, cars, even industrial machines are now connected IoT devices. Recent studies have predicted that by 2025 there will be over 75 billion of such IoT devices connected to the Internet. The providers of IoT based services want to integrate their services to satisfy customer requirements. For example, in the mobility scenario, different mobility solution providers want to offer a multi-modal ticket to their customers jointly. In such a distributed and loosely coupled environment, each owner and stakeholder wants to secure his/her own integrity, confidentiality, and functionality goals. This means that distributed rules and conditions defined by the individual owners must be enforced on the participating entities (e.g., customers or partners using their services). The owners and stakeholders may not necessarily trust each other's actions. Therefore, a mechanism is required that guarantees the rules and conditions specified by the different owners. Attacks on IoT devices and similar computing systems are increasing and getting more advanced. IoT devices are often constrained, i.e., they have limited processing power, memory, and energy. Security mechanisms designed for traditional computing systems, e.g., computers, servers, or mobile computing devices such as smartphones, may not fit in those constrained IoT devices. Weak security mechanisms and unenforced security measures were one of the main reasons for recent successful attacks on IoT devices and services. As IoT is now used in many sensitive places, including critical infrastructures, securing them becomes more critical than ever. This thesis focuses on developing mechanisms that secure IoT devices and services and enforcing the rules and conditions specified by the owners on entities that want to access owners' resources. In classical computer systems, security automata are used for specifying security policies and monitoring mechanisms are used for enforcing such policies. For instance, a reference monitor observes and stops the execution when the security policies are about to be violated, thus, the security policies are enforced. To restrict the adversary from using protected IoT devices or services for malicious purposes, it is required to ensure that a workflow must be followed to access the protected resource. In distributed IoT systems where the policies are governed by different owners, each owner would like to specify their rules and conditions in their workflows. The workflows contain tasks that must be performed in a particular order. The goal of this thesis is to develop mechanisms to specify and enforce these workflows in the distributed IoT environment. This thesis introduces a distributed WFAC framework that restricts the entities to do only what they are allowed to do in a collaborative environment. To gain access to a service protected by the WFAC framework, every workflow participant must prove that he/she is in a particular state of an authorized workflow. Authorized means two things: (a) the owner has authorized the workflow to be executed; (b) the workflow participant is authorized to execute it. This restricts the adversary's access to the devices and its services. The security policies defined by different owners are modeled as workflows and specified using Petri Nets. The policies are then enforced with the help of the WFAC framework which supports error-handling, accountability, integration of practitioner-friendly tools, and interoperability with existing security mechanisms such as OAuth. Thus, the WFAC guarantees the integrity of workflows in a distributed environment.}, language = {en} } @phdthesis{ParraRodriguez2019, author = {Parra Rodriguez, Juan David}, title = {Computational Resource Abuse in Web Applications}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus4-7706}, school = {Universit{\"a}t Passau}, pages = {xi, 158 Seiten}, year = {2019}, abstract = {Internet browsers include Application Programming Interfaces (APIs) to support Web applications that require complex functionality, e.g., to let end users watch videos, make phone calls, and play video games. Meanwhile, many Web applications employ the browser APIs to rely on the user's hardware to execute intensive computation, access the Graphics Processing Unit (GPU), use persistent storage, and establish network connections. However, providing access to the system's computational resources, i.e., processing, storage, and networking, through the browser creates an opportunity for attackers to abuse resources. Principally, the problem occurs when an attacker compromises a Web site and includes malicious code to abuse its visitor's computational resources. For example, an attacker can abuse the user's system networking capabilities to perform a Denial of Service (DoS) attack against third parties. What is more, computational resource abuse has not received widespread attention from the Web security community because most of the current specifications are focused on content and session properties such as isolation, confidentiality, and integrity. Our primary goal is to study computational resource abuse and to advance the state of the art by providing a general attacker model, multiple case studies, a thorough analysis of available security mechanisms, and a new detection mechanism. To this end, we implemented and evaluated three scenarios where attackers use multiple browser APIs to abuse networking, local storage, and computation. Further, depending on the scenario, an attacker can use browsers to perform Denial of Service against third-party Web sites, create a network of browsers to store and distribute arbitrary data, or use browsers to establish anonymous connections similarly to The Onion Router (Tor). Our analysis also includes a real-life resource abuse case found in the wild, i.e., CryptoJacking, where thousands of Web sites forced their visitors to perform crypto-currency mining without their consent. In the general case, attacks presented in this thesis share the attacker model and two key characteristics: 1) the browser's end user remains oblivious to the attack, and 2) an attacker has to invest little resources in comparison to the resources he obtains. In addition to the attack's analysis, we present how existing, and upcoming, security enforcement mechanisms from Web security can hinder an attacker and their drawbacks. Moreover, we propose a novel detection approach based on browser API usage patterns. Finally, we evaluate the accuracy of our detection model, after training it with the real-life crypto-mining scenario, through a large scale analysis of the most popular Web sites.}, subject = {Computersicherheit}, language = {en} } @phdthesis{Horaček2020, author = {Hor{\´a}ček, Jan}, title = {Algebraic and Logic Solving Methods for Cryptanalysis}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus4-7731}, school = {Universit{\"a}t Passau}, pages = {v, 154 Seiten}, year = {2020}, abstract = {Algebraic solving of polynomial systems and satisfiability of propositional logic formulas are not two completely separate research areas, as it may appear at first sight. In fact, many problems coming from cryptanalysis, such as algebraic fault attacks, can be rephrased as solving a set of Boolean polynomials or as deciding the satisfiability of a propositional logic formula. Thus one can analyze the security of cryptosystems by applying standard solving methods from computer algebra and SAT solving. This doctoral thesis is dedicated to studying solvers that are based on logic and algebra separately as well as integrating them into one such that the combined solvers become more powerful tools for cryptanalysis. This disseration is divided into three parts. In this first part, we recall some theory and basic techniques for algebraic and logic solving. We focus mainly on DPLL-based SAT solving and techniques that are related to border bases and Gr{\"o}bner bases. In particular, we describe in detail the Border Basis Algorithm and discuss its specialized version for Boolean polynomials called the Boolean Border Basis Algorithm. In the second part of the thesis, we deal with connecting solvers based on algebra and logic. The ultimate goal is to combine the strength of different solvers into one. Namely, we fuse the XOR reasoning from algebraic solvers with the light, efficient design of SAT solvers. As a first step in this direction, we design various conversions from sets of clauses to sets of Boolean polynomials, and vice versa, such that solutions and models are preserved via the conversions. In particular, based on a block-building mechanism, we design a new blockwise algorithm for the CNF to ANF conversion which is geared towards producing fewer and lower degree polynomials. The above conversions allow usto integrate both solvers via a communication interface. To reach an even tighter integration, we consider proof systems that combine resolution and polynomial calculus, i.e. the two most used proof systems in logic and algebraic solving. Based on such a proof system, which we call SRES, we introduce new types of solving algorithms that demostrate the synergy between Gr{\"o}bner-like and DPLL-like solving. At the end of the second part of the dissertation, we provide some experiments based on a new benchmark which illustrate that the our new method based on DPLL has the potential to outperform CDCL SAT solvers. In the third part of the thesis, we focus on practical attacks on various cryptograhic primitives. For instance, we apply SAT solvers in the case of algebraic fault attacks on the symmetric ciphers LED and derivatives of the block cipher AES. The main goal there is to derive so-called fault equations automatically from the hardware description of the cryptosystem and thus automatizate the attack. To give some extra power to a SAT solver that inverts the hash functions SHA-1 and SHA-2, we describe how to tweak the SAT solver using a programmatic interface such that the propagation of the solver and thus the attack itself is improved.}, subject = {Kryptoanalyse}, language = {en} }