An Integrated Approach of Threat Analysis for Autonomous Vehicles Perception System

Automated vehicles are a revolutionary step in mobility, providing safe and convenient riding experience while keeping the human-driving task minimal to none. Therefore, these intelligent equipped with sophisticated perception sensors (e.g., cameras radars), high-performance computers, artificial intelligence (AI)-driven algorithms, connectivity other internet-of-things (IoT) devices. This makes autonomous (AVs) special kind of cyber-physical system (CPS) that is moving at speed highly interactive dynamic environments public roads). Thus, AV potential target for cyber attackers weaponize, compromising safety mobility on road. The first addressing this problem have robust threat modeling framework can address evolving threats, especially applications. In regard, two areas studied paper: common practice automotive ISO/SAE 21434 standard, machine learning (ML) algorithms systems attacks. A comparative analysis an standard system-theoretic process security (STPA-Sec) approach also demonstrated paper. Based analysis, paper proposes risk assessment mathematical identify threats critical driving behaviors complex interactions AVs their operational design domain.