REMIND: A Framework for the Resilient Design of Automotive Systems
Published in IEEE Secure Development Conference, 2020
Recommended citation: T. Rosenstatter, K. Strandberg, R. Jolak, R. Scandariato, T. Olovsson, "REMIND: A Framework for the Resilient Design of Automotive Systems," 2020 IEEE Secure Development Conference (SecDev), Atlanta, GA, USA, 2020, pp. 81-95. https://doi.org/10.1109/SecDev45635.2020.00028
In the past years, great effort has been spent on enhancing the security and safety of vehicular systems. Current advances in information and communication technology have increased the complexity of these systems and lead to extended functionalities towards self-driving and more connectivity. Unfortunately, these advances open the door for diverse and newly emerging attacks that hamper the security and, thus, the safety of vehicular systems. In this paper, we contribute to supporting the design of resilient automotive systems. We review and analyze scientific literature on resilience techniques, fault tolerance, and dependability. As a result, we present the REMIND resilience framework providing techniques for attack detection, mitigation, recovery, and resilience endurance. Moreover, we provide guidelines on how the REMIND framework can be used against common security threats and attacks and further discuss the trade-offs when applying these guidelines.