How connected and automated vehicles (CAVs) are defended against cyberattacks by combining machine-learning intrusion detection with 5G-enabled cloud offloading, blockchain-based distributed trust across vehicles, roadside units and cloud, and quantum key distribution for securing key exchange between in-vehicle electronic control units. Students learn the threat landscape (DoS/DDoS, Sybil, spoofing, GPS deception, adversarial attacks on detectors) across V2X networks and why layered, interdisciplinary defenses are required.
A narrative review of collaborative, AI-driven approaches to securing connected and automated vehicles (CAVs). It surveys how machine-learning intrusion detection systems, 5G-enabled real-time data o…