As vehicles are being increasingly connected to the Internet and equipped with autonomous driving features, this increases the potential of cyberattacks and requires sophisticated implementations of resilience capable to detect attacks and react to them. Therefore, threat analysis and risk assessment including careful modelling of resilience are essential to prepare against cybersecurity risks. In this context, we extend by complementary monitoring/fallback mechanism our framework devoted to automatically discover complex cyberattack scenarios using abstract cost criteria. We then show that this extension allows analysing a realistic resilient model of cybersecurity aspects of a level 2 autonomous connected vehicle.
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