TY - JOUR A1 - De, Sangita A1 - Premek, Brada A1 - Mottok, Jürgen T1 - Derivation of Optimized Threshold of Semantic Alignment Metrics for Intepretation of Interoperability and Reusability of Cross-enterprise Vehicle Service Interface Models JF - Informatica N2 - Over the past decade, cars have turned gradually into real cyber physical systems. The collaboration of services between the service-oriented, cross-enterprise vehicle application frameworks has increased to generate novel, smart and complicated vehicle services. Consequently, from an interoperability perspective, semantically mapping of vehicle service component’s interface ontological models emerged as a big research interest in automotive application domain that manipulates several cross-enterprise synergy knowledge applications frameworks. The ontological metamodeling lays the foundation for building semantic bridge and exploring semantic associations between service components’ interface models based on the domain knowledge for semantic interoperability. Also, several semantic quality metrics has been defined over time for the vehicle service interface ontological metamodels. The empirically evaluated values of these metrics can be used to assess progress in cross-enterprise interoperability between the service and the clients’ APIs ontological models in vehicle domain. Despite potential benefits of semantic alignment quality metrics, the effective use of these metrics for vehicle service interface ontologies have proven elusive. Yes, such metrics can be used successfully for quantification, but then they mostly fail to provide adequate annotations in subsequent decision-making in the direction of semantic interoperability and reusability. The effective use of ontology semantic alignment quality metrics is basically hindered in the absence of the meaningful thresholds. In fact, the absence of an effective and meaningful threshold for the semantic similarity measure between various vehicle service interface ontological metamodels, motivates this research work which not only proposes a design approach to an optimized threshold for the semantic similarity metrics but also applies this threshold on few defined semantic alignment quality metrics. This paper also uses a real-world vehicle domain industrial case study to illustrate the design approach. KW - interface KW - automotive services KW - semantic KW - metrics KW - optimized threshold KW - framework KW - metamodels KW - ontologies Y1 - 2023 U6 - https://doi.org/10.31449/inf.v47i7.4739 SN - 0350-5596 VL - 47 IS - 7 PB - Slovenian Society Informatika ER - TY - INPR A1 - Linz, Tilo A1 - Mottok, Jürgen T1 - Application of Causal Models in Scenario-based Testing N2 - This paper presents a new methodology for scenario-based testing of automated driving functions in the context of ISO 21448 (safety of the target function). By using structural causal models (SCMs), the evaluation process of highly automated vehicle systems is to be improved, thus increasing their safety and reliability. Using SCMs, the presented methodology systematically analyzes causal relationships between various risk factors of the investigated system and its operating environment and automatically identifies potential parameter combinations that influence system safety. This approach makes it possible to safeguard automated driving functions, such as an emergency brake assistant, by determining foreseeable risks and providing them as test parameters for relevant scenarios. The HolmeS3 approach combines expert knowledge with probabilistic data analysis to develop robust causal models that can be validated through both simulation and real-world testing. The use of causal inference enables the generation of critical test cases, known as "edge and corner cases", which are essential for testing vehicle systems under investigation. This focused testing approach helps to limit the test case explosion that occurs with conventional approaches by specifically identifying highly relevant parameter combinations that potentially (negatively) influence system performance. The methodology presented, which was developed as part of the HolmeS3 R&D project, offers transparency, comparability, explainability and traceability in the modeling and testing processes. It supports compliance with the ISO 21448 standard and lays the foundation for the causality-driven development of safe and reliable automotive technology. The project's tools and methods can be applied beyond the automotive sector to all cyber-physical systems that require rigorous safety validation. Y1 - 2024 U6 - https://doi.org/10.13140/RG.2.2.34160.06402 ER - TY - CHAP A1 - Frauenschläger, Tobias A1 - Mottok, Jürgen T1 - Problems and New Approaches for Crypto-Agility in Operational Technology T2 - 12th European Congress Embedded Real Time Systems (ERTS 2024), 11-12 June 2024, Toulouse, France N2 - In recent years, cybersecurity has also become relevant for Operational Technology (OT). Critical systems like industrial automation systems or transportation systems are faced with new threats, and therefore require the implementation of thorough security measures. Regulations further mandate the deployment and regular verification of these security measures. However, OT systems differ from well-known systems of classic Information Technology (IT), such as mission times spanning decades, infrequent updates only during on-site maintenance, or diverse devices with varying support for security measures. The growing field of crypto-agility examines approaches to integrate security measures in an agile and flexible way, making updates easier and, therefore, encouraging a more frequent deployment of them. This paper contributes to this research field in the context of secure communication in two ways. We first examine the current state of crypto-agility by providing an overview of existing measures for OT systems. Then, we propose a new architecture concept with different deployment approaches to integrate security measures in a crypto-agile way. Based on a security library with a generic interface and a flexible proxy application, our architecture is capable of securing both new OT systems and existing ones via retrofit. Y1 - 2024 UR - https://www.researchgate.net/publication/383709526_Problems_and_New_Approaches_for_Crypto-Agility_in_Operational_Technology ER - TY - CHAP A1 - Schwind, Philipp A1 - Frauenschläger, Tobias A1 - Mottok, Jürgen T1 - Implementation of a Bump-in-the-Wire Security Gateway T2 - Proceedings of the 12th Prague Embedded Systems Workshop, June 27 - 29, 2024, Horoměřice, Czech Republic N2 - In the face of escalating cyber threats, the integration of Operational Technology (OT) with Information Technology (IT) systems presents heightened vulnerabilities to critical infrastructures. This paper focuses on the need for cybersecurity, showcasing the design and implementation of a security gateway to achieve bump-in-the-wire security between two units to be protected (assets). For that, each asset is assigned one security module that safeguards its communication paths. To ease bump-in-the-wire capability, the communication between the asset and the security-gateway must be stateless and operate on OSI layer 2. This is necessary to safeguard the whole communication bandwidth, regardless of the used protocols. For this objective, Linux-based packet sockets are used. An encrypted tunnel is established between two security gateways using the Datagram Transport Layer Security (DTLS) protocol. The results show that the implemented solution is capable of securing the asset’s network traffic without the need of any modifications. Y1 - 2024 UR - https://pesw.fit.cvut.cz/2024/PESW_2024.pdf SN - 978-80-01-07303-2 SP - 26 EP - 35 ER - TY - CHAP A1 - Horn, Luca A1 - Frauenschläger, Tobias A1 - Mottok, Jürgen T1 - Integration and Evaluation of Different FPGA based Hardware Accelerators for the AES Algorithm in the TLS Protocol to be Used in Critical Automation Systems T2 - 4. Symposium Elektronik und Systemintegration, Tagungsband: Symposium am 17. April 2024 Hochschule Landshut N2 - This thesis addresses the challenges of hardware-assisted cryptography in the context of automation systems in critical infrastructures. While hardware accelerators enhance cryptographic calculations in both performance and security, their permanence poses issues in adapting to evolving security concerns. To overcome this problem, we integrated and evaluated a hardware accelerator for the AES algorithm on an FPGA within a TLS application, comparing its performance with other accelerators. Employing a hybrid FPGA-CPU processor system, this setup achieves over 800 Mbit/s data rates, showcasing a more than 27 times acceleration in TLS transmissions compared to purely software-based solutions. The FPGA's flexibility and upgradability therefore make it an ideal platform for critical infrastructure, ensuring longevity and superior acceleration in TLS data transfers. Y1 - 2024 UR - https://www.haw-landshut.de/static/ITZ/Bilder/Cluster_MST/ESI_Symposium/ESI_2024/Tagungsband/1B2_Frauenschlaeger_OTH-R_TB-ESI2024_s18-27.pdf SN - 978-3-9818439-9-6 SP - 18 EP - 27 PB - Hochschule Landshut CY - Landshut ER - TY - CHAP A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Mottok, Jürgen A1 - Gruber, Hans T1 - Visual Expertise in Code Reviews: Using Holistic Models of Image Perception to Analyze and Interpret Eye Movements T2 - ETRA '23: 2023 Symposium on Eye Tracking Research and Applications, Tubingen Germany 30 May 2023- 2 June 2023 N2 - This study uses holistic models of image perception to analyze and interpret eye movements during a code review. 23 participants (15 novices and 8 experts) take part in the experiment. The subjects’ task is to review six short code examples in C programming language and identify possible errors. During the experiment, their eye movements are recorded by an SMI 250 REDmobile. Additional data is collected through questionnaires and retrospective interviews. The results implicate that holistic models of image perception provide a suitable theoretical background for the analysis and interpretation of eye movements during code reviews. The assumptions of these models are particularly evident for expert programmers. Their approach can be divided into different phases with characteristic eye movement patterns. It is best described as switching between scans of the code example (global viewing) and the detailed examination of errors (focal viewing). Y1 - 2023 U6 - https://doi.org/10.1145/3588015.3589189 SP - 1 EP - 7 PB - ACM ER - TY - JOUR A1 - Pozzobon, Enrico A1 - Weiß, Nils A1 - Mottok, Jürgen A1 - Matoušek, Václav T1 - An evolutionary fault injection settings search algorithm for attacks on safe and secure embedded systems JF - Neural Network World (NNW) Y1 - 2023 U6 - https://doi.org/10.14311/NNW.2023.33.020 VL - 33 IS - 5 SP - 357 EP - 374 PB - Czech Technical University in Prague ER - TY - CHAP A1 - Füreder, Lukas A1 - Mottok, Jürgen T1 - Assessment of a MACsec-based Security System for Use in Critical Infrastructure Communication T2 - Proceedings of the 12th Prague Embedded Systems Workshop, June 27 - 29, 2024, Horoměřice, Czech Republic N2 - This paper investigates the integration of Media Access Control Security (MACsec) into the communication of critical infrastructure, specifically within power grid applications, such as Substation Automation Systems (SAS) using the IEC 61850 standard. Building on the principles of both standards, this study aims to determine if MACsec can meet the security and performance requirements set by IEC 62351 for power system communications. Furthermore, a test environment containing a number of Intelligent Electronic Devices (IEDs) supporting communication compliant to all IEC 61850 message types is established to evaluate this integration. The results of the measurements executed in this environment indicate that MACsec could secure all types of messages, such as Manufacturing Message Specification (MMS), Sampled-Value (SV) and Generic Object Oriented Substation Events (GOOSE), within the required time periods without significant delays. Even with additional encryption activated in the cipher suite, the resulting transmission times are well below the required times. This suggests that MACsec can enhance the security goals for industrial communication by providing confidentiality in addition to the already mandated assurance of authenticity and integrity to all messages without compromising performance. Only the requirement for end-to-end security cannot be met by MACsec in this configuration, as the security system re-encrypts with every hop of the transmission. For this reason, we propose a hybrid approach of Transport Layer Security (TLS) and MACsec as part of future work. KW - MACsec KW - IEC61850 KW - IEC62351 KW - GOOSE KW - Secure Communication Y1 - 2024 UR - https://pesw.fit.cvut.cz/2024/PESW_2024.pdf SN - 978-80-01-07303-2 SP - 51 EP - 59 ER - TY - CHAP A1 - Bittner, Dominik A1 - Hendricks, Ricky-Ricardo A1 - Horn, Luca A1 - Mottok, Jürgen T1 - In-depth Benchmarking of Transfer Learning Techniques for Improved Bottle Recognition T2 - 2023 IEEE 13th International Conference on Pattern Recognition Systems (ICPRS), Guayaquil, Ecuador, 04-07 July 2023 N2 - An immense diversity in bottle types requires high accuracy during sorting for recycling purposes by breweries. This extremely complex and time-consuming procedure can result in enormous additional costs for them. This paper presents transfer learning-based algorithms for classifying beer bottle brands using camera images, applicable in individual sorting solutions for different use cases. The problem is tackled using customised EfficientNet, InceptionResNet and VGG models along with an augmented dataset. In addition, a detailed analysis of different model and parameter combinations is performed, enabling tailor-made technologies for specific conditions and resource limitations. In accompanying validations and subsequent tests, a test accuracy of 100% in the recognition of beer brands could be achieved, proving the proposed method fully contributes to the solution of the problem. KW - Analytical models KW - Costs KW - Transfer learning KW - Benchmark testing KW - Cameras KW - Pattern recognition KW - Recycling Y1 - 2023 SN - 979-8-3503-3337-4 U6 - https://doi.org/10.1109/ICPRS58416.2023.10178995 SP - 1 EP - 6 PB - IEEE ER - TY - CHAP A1 - Röhrl, Simon A1 - Staufer, Susanne A1 - Nadimpalli, Vamsi Krishna A1 - Bugert, Flemming A1 - Bugert, Flemming A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Bittner, Dominik A1 - Ezer, Timur A1 - Mottok, Jürgen T1 - PYTHIA - AI SUGGESTED INDIVIDUAL LEARNING PATHS FOR EVERY STUDENT T2 - INTED2024 Proceedings: 18th International Technology, Education and Development Conference, Valencia, Spain. 4-6 March, 2024 N2 - During the COVID-19 pandemic, the importance of digital course rooms, where teachers provide their learning materials, increased dramatically. While these platforms are crucial for providing teaching materials, they often fall short in addressing individual student needs. A system within an academic setting, capable of creating and presenting individual learning paths for each student, can solve these issues. These paths are composed of various learning elements - defined in our previous work as units of educational content with which a learner works. Currently, there is no suitable system that enables the integration of learning path generating algorithms into a digital course room. Therefore we present an application that enables this integration into the Moodle Learning Management System (LMS). More precisely, this paper presents a Moodle plugin together with its framework. It describes the mechanism for effectively collecting data from Moodle, which AI algorithms then use to generate personalized learning paths. Subsequently these paths are visualized with the help of the Moodle plugin. We started with a set of requirements and use cases for the interface connecting Moodle to the AI system, which were established with a group of experts. Based on the requirements, various relevant technologies were assessed, and the best ones were chosen for implementation. Following that, the paper develops a strategy for software structuring as well as an architecture, focusing on performance, modularity, and ease of deployment for widespread use. Furthermore, the architecture ensures a simple method for integrating the algorithms. Afterwards, the framework's concrete implementation is described. A technique for enriching learning elements with metadata is presented, and additionally a concept for presenting these learning elements within a hierarchy. Moreover, it is shown how questionnaire responses and learning analytics are utilized for data collection. We cover in detail techniques for extracting and storing data from the Moodle database, as well as methods for customizing Moodle course rooms and a standard API for incorporating AI algorithms. Finally, the paper discusses the application of the proposed framework in an actual course and how student feedback is collected, which could enhance the framework. It concludes with an assessment of the outcomes obtained and prospects for the framework's future advancements. KW - Personalized Learning Paths KW - Learning Management System KW - Software Architecture KW - Moodle KW - Artificial Intelligence Y1 - 2024 SN - 978-84-09-59215-9 U6 - https://doi.org/10.21125/inted.2024.0783 SN - 2340-1079 SP - 2871 EP - 2880 ER - TY - JOUR A1 - Fuxen, Philipp A1 - Schönhärl, Stefan A1 - Schmidt, Jonas A1 - Gerstner, Mathias A1 - Jahn, Sabrina A1 - Graf, Julian A1 - Hackenberg, Rudolf A1 - Mottok, Jürgen T1 - A Cybersecurity Education Platform for Automotive Penetration Testing JF - International Journal On Advances in Security N2 - The paper presents a penetration testing framework for automotive IT security education and evaluates its realization. The automotive sector is changing due to automated driving functions, connected vehicles, and electric vehicles. This development also creates new and more critical vulnerabilities. This paper addresses a possible countermeasure, automotive IT security education. Some existing solutions are evaluated and compared with the created Automotive Penetration Testing Education Platform (APTEP) framework. In addition, the APTEP architecture is described. It consists of three layers representing different attack points of a vehicle. The realization of the APTEP is a hardware case and a virtual platform referred to as the Automotive Network Security Case (ANSKo). The hardware case contains emulated control units and different communication protocols. The virtual platform uses Docker containers to provide a similar experience over the internet. Both offer two kinds of challenges. The first introduces users to a specific interface, while the second combines multiple interfaces, to a complex and realistic challenge. This concept is based on modern didactic theories, such as constructivism and problem-based/challenge-based learning. Computer Science students from the Ostbayerische Technische Hochschule (OTH) Regensburg experienced the challenges as part of a elective subject. In an online survey evaluated in this paper, they gave positive feedback. Also, a part of the evaluation is the mapping of the ANSKo and the maturity levels in the Software Assurance Maturity Model (SAMM) practice Education & Guidance as well as the SAMM practice Security Testing. The scientific contribution of this paper is to present an APTEP, a corresponding learning concept and an evaluation method. KW - Challenge-based Learning KW - Education Framework KW - Penetration Testing KW - Automotive KW - IT-Security Education Y1 - 2022 UR - http://www.iariajournals.org/security/sec_v15_n34_2022_paged.pdf SN - 1942-2636 VL - 15 IS - 3&4 SP - 106 EP - 118 PB - IARIA ER - TY - CHAP A1 - Staufer, Susanne A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Bittner, Dominik A1 - Nadimpalli, Vamsi Krishna A1 - Bugert, Flemming A1 - Ezer, Timur A1 - Röhrl, Simon A1 - Mottok, Jürgen T1 - Learning elements in LMS - a survey among students T2 - INTED2024 Proceedings: 18th International Technology, Education and Development Conference, Valencia, Spain. 4-6 March, 2024 N2 - In higher education, improving learning and learning success are goals of general improvement. Lecturers teaches content and students acquire that content in an efficient way. To structure content, learning element categories are evaluated from the student's point of view in higher education area. The aim is to validate given definitions of ten learning element categories within a Learning Management System (LMS). This paper evaluates a categorization of learning elements for organizing learning content in online education within LMSs. Therefore, ten categories of learning elements and corresponding definitions were defined in a previous work as base for this paper. The learning elements to examine are manuscript, exercise, quiz, brief overview, learning goal, summary, collaboration tool, auditory additional material, textual additional material, and visual additional material. To validate the definitions and to get improvements to each learning element a survey is processed. Beside the demographic data questions, the survey consists of two questions to the acceptance of the definitions and asks for improvements. 148 students between the ages 19 and 35 participate in the survey in summer term 2023. The education level of the participants ranges from undergraduates to Ph.D. students. The results of this paper are that more than 80% accept the given definitions. Some definitions of the learning elements are changed, but the changes are restricted to additions of maximal four words. This categorization of learning elements could lead to improvements in learning by giving the content more structure. With the structure students get the possibility to learn with preferred learning elements which could lead to more success in learning and to a decreasing dropout rate in universities. In the future, the learning elements allow to classify content within LMSs with the goal of generating individual learning paths. Furthermore, our project will integrate these learning elements, use them to generate learning paths, and could set a new standard in the way of personalized learning. KW - Learning elements KW - learning management system KW - learning objects KW - questionnaire KW - higher education area KW - content organization Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-71135 SN - 978-84-09-59215-9 SN - 2340-1079 SP - 4224 EP - 4231 PB - IATED ER - TY - CHAP A1 - Grabinger, Lisa A1 - Ezer, Timur A1 - Hauser, Florian A1 - Mottok, Jürgen T1 - The impact of eyenalyzer T2 - ICERI2024 Proceedings: 17th Annual International Conference of Education, Research and Innovation, 11th-13th November 2024, Seville, Spain N2 - Empirical research poses numerous challenges for beginners. This is especially true for data analysis – a task that usually requires knowledge from two distinct areas: statistics and programming. To support prospective researchers with that task, we developed a web-based tool called eyenalyzer. It supports common activities in the data analysis phase of empirical studies in a way that is suitable for novices in both, statistics and programming. The present article describes a controlled experiment investigating the impact of this tool with a total of 20 participants. All of them are given a set of common data analysis tasks. Half of the participants complete the tasks using eyenalyzer, the other half can use anything except for eyenalyzer. For each task and participant, we record the time in minutes, the task score, and the perceived difficulty. The results confirm that our tool is a valuable support for novice researchers: With eyenalyzer, the participants are significantly faster, achieve higher scores, and perceive the tasks to be less difficult. KW - tool evaluation KW - data analysis KW - eye tracking KW - empirical research Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-78215 SN - 978-84-09-63010-3 SN - 2340-1095 SP - 695 EP - 701 PB - IATED ER - TY - CHAP A1 - Jahn, Sabrina A1 - Weiss, Nils A1 - Akcakoca, Ugur A1 - Mottok, Jürgen ED - Gómez Chova, Luis ED - López Martínez, A. ED - Candel Torres, I. T1 - Under The Hood - A Concept for Virtualized Automotive Security Education T2 - EDULEARN21: Proceedings, 13th International Conference on Education and New Learning Technologies, Online Conference. 5-6 July, 2021 N2 - In recent years, our society faced a massive interconnection of computer-based everyday objects, which opens these items for cyber-attacks. Dependent on the physical capabilities, successful attacks can vary from data exposure or a loss of functionality to a threat to life and limb. Connected- and autonomous vehicles are extremely safety-critical systems with a huge damage potential. This global trend, together with existing and upcoming regulations (ISO 270xx, ISO 21434, UNECE WP.29, UNECE R155), and the lack of qualified professionals create a tension field for the entire automotive industry. Hence, new education concepts for engineers of safety-critical and connected systems are necessary to secure our daily and future systems against cyber-attacks and raise awareness and knowledge of the topic of IT-Security. Existing automotive security education systems have one common problem: All systems are hardware-based and therefore have very steep learning curves for beginners. Hardware-based systems, in general, are expensive in their initial costs, require regular maintenance, and add diverse operational difficulties independent of the aspired education goal. Additionally, the global pandemic increased the necessity of virtual education concepts for security training in cyber-physical systems. Therefore, we present a novel concept for the education of cyber-security professionals for automotive systems based on discovery and problem-based learning in a virtual learning environment (VLE). Our concept contains individual exercises focusing on the topics of vulnerabilities and attacks in automotive networks and systems. Each exercise relates those topics to the corresponding security goals and countermeasures for mitigation. The learners work collaboratively in a self-contained manner within the VLE to acquire the necessary information to answer questions or find a solution to the given problem. To consider the heterogeneous background (e.g. knowledge, experience, preconceptions) of the learners, the topics can be presented in different difficulties, enabling an adaptable learning environment and different learning trajectories within the exercises. The concept is based on a VLE, consisting of automotive networks and components, which simulate the behavior of a vehicle. This environment provides a hands-on, "real-life" scenario, which allows discovery and problem-based learning in a realistic, but cheap and scalable education environment. Furthermore, virtualization removes common difficulties, always present in training on real hardware. This aims to decrease complexity, prevent learning obstacles related to hardware handling, and enables a location-independent learning environment. The target group of our education concept is Bachelor and Master students of computer science, engineering (e.g. electrical engineering, mechatronics), or similar studies, and (experienced) engineers from the industry. In summary, our publication contains two contributions. We present an adaptable virtual learning environment for automotive security education, combined with an educational concept based on discovery and problem-based learning techniques. The goals of our concept are the education of cyber-security professionals for safety-critical, connected automotive systems and the support of life-long learning reaching from academic education to training in the industry. KW - automotive systems KW - discovery learning KW - higher education KW - inductive teaching KW - problem-based learning KW - security education KW - virtual learning environment Y1 - 2021 SN - 978-84-09-31267-2 U6 - https://doi.org/10.21125/edulearn.2021.1231 SN - 2340-1117 SP - 6109 EP - 6118 ER -