This course provides an exploration of the intersection between Artificial Intelligence, Cybersecurity, and Cyber-Physical Systems, with a primary focus on the automotive domain. As vehicles transition toward Software-Defined Vehicles (SDVs) and high-level autonomy, the attack surface expands from local bus architectures (CAN/Ethernet) to cloud-based APIs and V2X (Vehicle-to-Everything) networks. Students will study the security of perception systems (LiDAR, Camera, Radar), the resilience of AI models against adversarial machine learning, and the regulatory landscape governing automotive safety and security (ISO 21434, UN ECE R155).
Some of the learning objectives include: (1) Identify and mitigate security vulnerabilities in the CAV electronic architecture. (2) Apply cryptographic principles and secure hardware mechanisms (HSM, Secure Boot) to automotive systems. (3) Critically evaluate research papers on adversarial machine learning and sensor spoofing. (4) Navigate the standards and regulations required for automotive type approval.