Abstract
Autonomous Vehicles rely heavily on their sensors’ information to navigate correctly. Autonomous driving requires the support of infrastructure-based systems to provide extra sensor information, which cannot be collected by vehicles. We expect that such infrastructure-based systems are typically not provided by the same manufacturer as the vehicle using them. In this paper, we propose a first of its kind, compositional threat analysis and risk assessment method, called C-TAR, and illustrate the method using a simplified example from an autonomous driving context. The proposed method extends a common threat and risk analysis method by statements of dependency on interfacing systems and provides a compatibility check of two systems working together. C-TAR allows the user to identify whether two independently developed systems can interact together securely based on the extended threat and risk analysis.
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Acknowledgements
The authors would like to thank all partners within the Hi-Drive project for their cooperation and valuable contribution. [This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101006664. The sole responsibility of this publication lies with the authors. Neither the European Commission nor CINEA - in its capacity of Granting Authority - can be made responsible for any use that may be made of the information this document contains.]
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Abdelsalam, M., Greiner, S., Aktouf, OEK., Mercier, A. (2024). C-TAR: A Compositional Threat Analysis and Risk Assessment Method for Infrastructure-Based Autonomous Driving. In: Katsikas, S., et al. Computer Security. ESORICS 2023 International Workshops. ESORICS 2023. Lecture Notes in Computer Science, vol 14399. Springer, Cham. https://doi.org/10.1007/978-3-031-54129-2_10
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DOI: https://doi.org/10.1007/978-3-031-54129-2_10
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