TY - JOUR A1 - Schüle, Maximilian E. A1 - Schliski, Pascal M. N. A1 - Hutzelmann, Thomas A1 - Rosenberger, Tobias A1 - Leis, Viktor A1 - Vorona, Dimitri A1 - Kemper, Alfons A1 - Neumann, Thomas T1 - Monopedia: Staying Single is Good Enough – The HyPer Way for Web Scale Applications JF - Proceedings of the VLDB Endowment UR - https://doi.org/10.14778/3137765.3137809 Y1 - 2017 UR - https://doi.org/10.14778/3137765.3137809 SN - 2150-8097 VL - 10 IS - 12 SP - 1921 EP - 1924 PB - ACM CY - New York ER - TY - CHAP A1 - Bayerl, Dominik A1 - Hutzelmann, Thomas A1 - Hof, Hans-Joachim T1 - Efficient Cross-Architecture Binary Function Embeddings through Knowledge Distillation T2 - Proceedings of the 11th ACM Cyber-Physical System Security Workshop N2 - Deep learning has recently been shown to be effective in various tasks related to static binary analysis. One important analysis task is the binary function similarity problem: Given the binary code of two functions compiled with different compilers, different settings, and different processor architectures, the goal is to decide whether the functions are semantically equivalent (i.e. "similar") or not. This problem has numerous applications for embedded systems, for example plagiarism detection, validation of compliance restrictions with usable software licenses, more efficient reverse engineering of existing binary codebases, or vulnerability scanning by detecting known vulnerable functions. In this paper, we propose a novel training scheme for the popular transformer neural network architecture to learn function embeddings directly from instruction listings. Unlike existing approaches, our solution explicitly considers the cross-architecture scenario: we propose a training method to adapt the model to different instruction set architectures (ISA) without having to train a new model from scratch, which allows the model to also be used efficiently for embedded systems, where there are a variety of different processor architectures. We show that our solution achieves a similarity classification accuracy of 89.6% on a dataset consisting of several real-world open source software projects. Finally, we conduct extensive experiments to demonstrate the effectiveness of knowledge distillation in increasing the computational efficiency of the embedding model. We demonstrate a reduction in the number of parameters from 87M to 23M, while still maintaining a classification accuracy of 87.8%. Our code and artifacts are available as open source. UR - https://doi.org/10.1145/3709017.3737709 Y1 - 2025 UR - https://doi.org/10.1145/3709017.3737709 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-61584 SN - 979-8-4007-1413-9 SP - 43 EP - 51 PB - ACM CY - New York ER - TY - JOUR A1 - Hutzelmann, Thomas A1 - Mauksch, Dominik A1 - Petrovska, Ana A1 - Pretschner, Alexander T1 - Generation of Tailored and Confined Datasets for IDS Evaluation in Cyber-Physical Systems JF - IEEE Transactions on Dependable and Secure Computing N2 - The state-of-the-art evaluation of an Intrusion Detection System (IDS) relies on benchmark datasets composed of the regular system's and potential attackers’ behavior. The datasets are collected once and independently of the IDS under analysis. This paper questions this practice by introducing a methodology to elicit particularly challenging samples to benchmark a given IDS. In detail, we propose (1) six fitness functions quantifying the suitability of individual samples, particularly tailored for safety-critical cyber-physical systems, (2) a scenario-based methodology for attacks on networks to systematically deduce optimal samples in addition to previous datasets, and (3) a respective extension of the standard IDS evaluation methodology. We applied our methodology to two network-based IDSs defending an advanced driver assistance system. Our results indicate that different IDSs show strongly differing characteristics in their edge case classifications and that the original datasets used for evaluation do not include such challenging behavior. In the worst case, this causes a critical undetected attack, as we document for one IDS. Our findings highlight the need to tailor benchmark datasets to the individual IDS in a final evaluation step. Especially the manual investigation of selected samples from edge case classifications by domain experts is vital for assessing the IDSs. UR - https://doi.rog/10.1109/TDSC.2023.3341211 Y1 - 2023 UR - https://doi.rog/10.1109/TDSC.2023.3341211 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-54670 SN - 1941-0018 VL - 21 IS - 4 SP - 3948 EP - 3962 PB - IEEE CY - New York ER - TY - JOUR A1 - Petrovska, Ana A1 - Kugele, Stefan A1 - Hutzelmann, Thomas A1 - Beffart, Theo A1 - Bergemann, Sebastian A1 - Pretschner, Alexander T1 - Defining adaptivity and logical architecture for engineering (smart) self-adaptive cyber–physical systems JF - Information and Software Technology UR - https://doi.org/10.1016/j.infsof.2022.106866 Y1 - 2022 UR - https://doi.org/10.1016/j.infsof.2022.106866 SN - 0950-5849 VL - 2022 IS - 147 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Petrovska, Ana A1 - Hutzelmann, Thomas A1 - Kugele, Stefan T1 - A Theoretical Framework for Self-Adaptive Systems: Specifications, Formalisation, and Architectural Implications T2 - SAC '23: Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing UR - https://doi.org/10.1145/3555776.3577665 KW - self-adaptive systems KW - theoretical framework KW - minimum requirements KW - formalisation KW - architectural implication Y1 - 2023 UR - https://doi.org/10.1145/3555776.3577665 SN - 978-1-4503-9517-5 SP - 1440 EP - 1449 PB - ACM CY - New York ER - TY - CHAP A1 - Zieglmeier, Valentin A1 - Kacianka, Severin A1 - Hutzelmann, Thomas A1 - Pretschner, Alexander T1 - A Real-Time Remote IDS Testbed for Connected Vehicles T2 - Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing UR - https://doi.org/10.1145/3297280.3297465 Y1 - 2019 UR - https://doi.org/10.1145/3297280.3297465 SN - 978-1-4503-5933-7 SP - 1898 EP - 1905 PB - ACM CY - New York ER - TY - CHAP A1 - Lipp, Stephan A1 - Elsner, Daniel A1 - Hutzelmann, Thomas A1 - Banescu, Sebastian A1 - Pretschner, Alexander A1 - Böhme, Marcel T1 - FuzzTastic: A Fine-grained, Fuzzer-agnostic Coverage Analyzer T2 - Proceedings, 2022 ACM/IEEE 44th International Conference on Software Engineering: Companion Proceedings N2 - Performing sound and fair fuzzer evaluations can be challenging, not only because of the randomness involved in fuzzing, but also due to the large number of fuzz tests generated. Existing evaluations use code coverage as a proxy measure for fuzzing effectiveness. Yet, instead of considering coverage of all generated fuzz inputs, they only consider the inputs stored in the fuzzer queue. However, as we show in this paper, this approach can lead to biased assessments due to path collisions. Therefore, we developed FuzzTastic, a fuzzeragnostic coverage analyzer that allows practitioners and researchers to perform uniform fuzzer evaluations that are not affected by such collisions. In addition, its time-stamped coverage-probing approach enables frequency-based coverage analysis to identify barely tested source code and to visualize fuzzing progress over time and across code. To foster further studies in this field, we make FuzzTastic, together with a benchmark dataset worth ~12 CPU-years of fuzzing, publicly available; the demo video can be found at https://youtu.be/Lm-eBx0aePA. UR - https://doi.org/10.1145/3510454.3516847 Y1 - 2022 UR - https://doi.org/10.1145/3510454.3516847 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-54624 SN - 978-1-4503-9223-5 SP - 75 EP - 79 PB - ACM CY - New York ER - TY - JOUR A1 - Hutzelmann, Thomas A1 - Banescu, Sebastian A1 - Pretschner, Alexander T1 - A Comprehensive Attack and Defense Model for the Automotive Domain JF - SAE International Journal of Transportation Cybersecurity and Privacy UR - https://doi.org/10.4271/11-02-01-0001 Y1 - 2019 UR - https://doi.org/10.4271/11-02-01-0001 SN - 2572-1054 VL - 2 IS - 1 PB - SAE International CY - Warrendale ER - TY - INPR A1 - Ognawala, Saahil A1 - Pretschner, Alexander A1 - Hutzelmann, Thomas A1 - Psallida, Eirini A1 - Amato, Ricardo Nales T1 - Reviewing KLEE’s Sonar-Search Strategy in Context of Greybox Fuzzing N2 - Automatic test-case generation techniques of symbolic execution and fuzzing are the most widely used methods to discover vulnerabilities in, both, academia and industry. However, both these methods suffer from fundamental drawbacks that stop them from achieving high path coverage that may, consequently, lead to discovering vulnerabilities at the numerical scale of static analysis. In this presentation, we examine systems-under-test (SUTs) at the granularity level of functions and postulate that achieving higher function coverage (execution of functions in a program at least once) than, both, symbolic execution and fuzzing may be a necessary condition for discovering more vulnerabilities than both. We will start this presentation with the design of a targeted search strategy for KLEE, sonar-search, that prioritizes paths leading to a target function, rather than maximizing overall path coverage in the program. Then, we will show that examining SUTs at the level of functions (compositional analysis) leads to discovering more vulnerabilities than symbolic execution from a single entry point. Using this finding, we will, then, demonstrate a greybox fuzzing method that can achieve higher function coverage than symbolic execution. Finally, we will present a framework to effectively manage vulnerabilities and assess their severities. UR - https://doi.org/10.48550/arXiv.1803.04881 Y1 - 2018 UR - https://doi.org/10.48550/arXiv.1803.04881 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-54646 PB - arXiv CY - Ithaca ER - TY - CHAP A1 - Ognawala, Saahil A1 - Hutzelmann, Thomas A1 - Psallida, Eirini A1 - Pretschner, Alexander T1 - Improving Function Coverage with Munch: A Hybrid Fuzzing and Directed Symbolic Execution Approach T2 - Proceedings of the 33rd Annual ACM Symposium on Applied Computing UR - https://doi.org/10.1145/3167132.3167289 Y1 - 2018 UR - https://doi.org/10.1145/3167132.3167289 SN - 978-1-4503-5191-1 SP - 1475 EP - 1482 PB - ACM CY - New York ER - TY - CHAP A1 - Hutzelmann, Thomas A1 - Mauksch, Dominik A1 - Pretschner, Alexander ED - Muccini, Henry ED - Avgeriou, Paris ED - Buhnova, Barbora ED - Camara, Javier ED - Caporuscio, Mauro ED - Franzago, Mirco ED - Koziolek, Anne ED - Scandurra, Patrizia ED - Trubiani, Catia ED - Weyns, Danny ED - Zdun, Uwe T1 - How to Conduct Experiments with a Real Car? Experiences and Practical Guidelines T2 - Software Architecture: 14th European Conference, ECSA 2020, Tracks and Workshops, L'Aquila, Italy, September 14–18, 2020, Proceedings UR - https://doi.org/10.1007/978-3-030-59155-7_37 Y1 - 2020 UR - https://doi.org/10.1007/978-3-030-59155-7_37 SN - 978-3-030-59155-7 SP - 518 EP - 526 PB - Springer CY - Cham ER - TY - THES A1 - Hutzelmann, Thomas T1 - A Holistic Methodology for Quality Assessment of Intrusion Detection Systems T2 - Eine Ganzheitliche Methodik zur Qualitätsbewertung von Intrusion Detection Systemen Y1 - 2024 UR - https://mediatum.ub.tum.de/1747236 PB - Technische Universität München CY - München ER - TY - CHAP A1 - Ullrich, Henning A1 - Bayerl, Dominik A1 - Hutzelmann, Thomas A1 - Hof, Hans-Joachim T1 - Application of Quantum Key Distribution in Intelligent Transport Systems T2 - Proceedings of the 2nd Cyber Security in CarS Workshop (CSCS’25) N2 - Quantum Key Distribution (QKD) enables two parties to generate a secret key, based on quantum physical properties. The secrecy of the exchanged key is guaranteed by these quantum physical properties, even against an attacker using a quantum computer. QKD therefore offers an Quantum Information Theoretically Secure (Q-ITS) alternative to Post Quantum Cryptography (PQC) schemes. This paper discusses advantages and challenges of deploying a QKD system in an Intelligent Transport System (ITS), by examining two exemplary use cases. Approaches to effectively implement QKD in these use cases are proposed, with a short discussion of advantages over the use of classical and PQC schemes. UR - https://doi.org/10.1145/3736130.3762692 Y1 - 2025 UR - https://doi.org/10.1145/3736130.3762692 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-63186 SN - 979-8-4007-1928-8 PB - ACM CY - New York ER - TY - CHAP A1 - Laves, Claudius A1 - Hutzelmann, Thomas A1 - Mayer, Kevin A1 - Hof, Hans-Joachim T1 - Driving Down Premiums: A Security and Forensic Analysis of the DriveWell Insurance System T2 - Proceedings of the 2nd Cyber Security in CarS Workshop (CSCS’25) N2 - Modern car insurance companies can dynamically adjust premiums with mobile sensor units that constantly record, analyze, and grade driving behavior. However, attackers can tamper with these systems to cheat the insurance company and reduce their premiums. We developed an attacker model for this threat in conjunction with a risk assessment using the ISO/SAE 21434 Risk Rating Methodology, a widely accepted standard for evaluating and managing risks in automotive systems. To support and showcase our model, we examined the static IT security of the mobile sensor unit DriveWell and its companion Android application HUK Mein Auto. In particular, we utilized digital forensic tools to analyze the stored data in the sensor’s internal storage and the app’s smartphone storage, with a focus on encryption mechanisms for locally stored data and internet communication. During this analysis, we spotted a critical vulnerability that enables attackers to manipulate their insurance scores and potentially reduce premiums by up to 30%. Our model and real-world analysis provide a solid foundation for reducing the risk of such manipulation of insurance premiums. UR - https://doi.org/10.1145/3736130.3762688 Y1 - 2025 UR - https://doi.org/10.1145/3736130.3762688 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-64728 SN - 979-8-4007-1928-8 PB - ACM CY - New York ER - TY - INPR A1 - Löw, Jakob A1 - Vasu Ashoka, Vishwa Vimukthi A1 - Hutzelmann, Thomas A1 - Hof, Hans-Joachim T1 - Security Aspects of ISO 15118 Plug and Charge Payment UR - https://doi.org/10.48550/arXiv.2512.15966 Y1 - 2025 UR - https://doi.org/10.48550/arXiv.2512.15966 PB - arXiv CY - Ithaca ER -