TY - CHAP A1 - Michl, Marco A1 - Hof, Hans-Joachim A1 - Katzenbeisser, Stefan T1 - Classification, Impact, and Mitigation Strategies of Attacks in Automotive Trust Management Systems T2 - Proceedings of the 2024 on Cyber Security in CarS Workshop (CSCS ’24) N2 - 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. UR - https://doi.org/10.1145/3689936.3694691 Y1 - 2024 UR - https://doi.org/10.1145/3689936.3694691 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-53694 SN - 979-8-4007-1232-6 SP - 61 EP - 75 PB - ACM CY - New York ER - TY - CHAP A1 - Michl, Marco A1 - Hof, Hans-Joachim A1 - Katzenbeisser, Stefan T1 - From Access to Trust: Policy-Based Automotive Trust Management With XACML T2 - Proceedings of the 2nd Cyber Security in CarS Workshop (CSCS’25) N2 - Trust is a fundamental requirement in vehicular systems, particularly in the context of autonomous and cooperative driving, where decisions often depend on data received from other vehicles or infrastructure. This paper presents a novel approach to integrating trust-based reasoning—specifically, decision-making based on subjective logic—into Attribute-Based Access Control (ABAC) systems, using the XACML policy language. We draw a parallel between trust management and access control, showing that trust assessments can be modeled as access decisions and expressed through standard access control policies. This integration allows for the reuse of mature ABAC infrastructure to represent and enforce trust-based decisions. Furthermore, we demonstrate how trust discounting mechanisms, which combine node-based and data-based trust, can be implemented within XACML policies. To evaluate this approach, we introduce a Rust-based XACML engine capable of interpreting trust-enhanced policies. Its integration in both inter- and intra-vehicle scenarios is discussed, assuming a modern zone-based architecture. Our results suggest that policy-based trust management can be efficiently implemented, enabling flexible and standardized trust reasoning in automotive environments. UR - https://doi.org/10.1145/3736130.3764511 Y1 - 2025 UR - https://doi.org/10.1145/3736130.3764511 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-64731 SN - 979-8-4007-1928-8 PB - ACM CY - New York ER -