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C-TAR: A Compositional Threat Analysis and Risk Assessment Method for Infrastructure-Based Autonomous Driving

Authors: Mohamed Abdelsalam; Simon Greiner; Oum-El-Kheir Aktouf; Annabelle Mercier;

C-TAR: A Compositional Threat Analysis and Risk Assessment Method for Infrastructure-Based Autonomous Driving

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. https://doi.org/10.1007/978-3-031-54129-2_10

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Keywords

IoT, C-ITS, Autonomous vehicles, Compositionality, Automotive Security, Smart Infrastructure

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Average
Average
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