@inproceedings{MichlHof2024, author = {Michl, Marco and Hof, Hans-Joachim}, title = {Towards a Stakeholder-Centric Trust Management Approach for the Automotive Ecosystem}, booktitle = {SECURWARE 2024: The Eighteenth International Conference on Emerging Security Information, Systems and Technologies}, editor = {Hussain, Fatima and Fries, Steffen}, publisher = {IARIA}, address = {[s. l.]}, isbn = {978-1-68558-206-7}, url = {https://www.thinkmind.org/library/SECURWARE/SECURWARE_2024/securware_2024_2_70_30036.html}, pages = {64 -- 70}, year = {2024}, language = {en} } @inproceedings{MichlHofKatzenbeisser2024, author = {Michl, Marco and Hof, Hans-Joachim and Katzenbeisser, Stefan}, title = {Classification, Impact, and Mitigation Strategies of Attacks in Automotive Trust Management Systems}, booktitle = {Proceedings of the 2024 on Cyber Security in CarS Workshop (CSCS '24)}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-1232-6}, doi = {https://doi.org/10.1145/3689936.3694691}, pages = {61 -- 75}, year = {2024}, abstract = {With the advent of connected vehicles, which provide many new comfort functions, the attack surface increased as well. Widespread "hard security" mechanisms are used to secure the vehicle and its infrastructure, but they cannot mitigate all threats, especially if inside attackers are considered. "Soft security" mechanisms, like trust and reputation systems, can help to close the attack surface further. However, such systems add complexity and can also lead to further vulnerabilities. To use such mechanisms securely, this work analyzes attacks targeting trust management systems in the automotive domain. For this purpose, a literature review was conducted, and the extracted attacks were characterized and divided into several clusters, introducing a new nomenclature of attacks against trust management for vehicles. We argue that four main categories of attacks exist. They are distinguished by their target component: communication channel, trust management layer, or application. As a fourth category, we see attacks that are enabled by the use of trust management systems. The outcome of this analysis was used to create an adversary model based on detected attack vectors and to define abstract reference attackers. These can be used to evaluate the resilience of automotive trust management systems against the analyzed attacks. Mitigation strategies against the adversary's capabilities are further presented to avoid vulnerabilities in the design of automotive trust management systems.}, language = {en} }