Cybersecurity Risk Management in Cooperative Intelligent Transport Systems

Vehicles have been connected for decades through over-the-air updates, infotainment systems, Wi–Fi, and Bluetooth interfaces. The emergence of cooperative intelligent transport systems (C-ITS) as the next generation of intelligent transport systems (ITS) has greatly expanded this connectivity. C-ITS is a key enabler for autonomous driving, providing real-time coordination between vehicles and infrastructure. By linking vehicles, infrastructure, road users, and cloud platforms through vehicle-to-everything (V2X) communication, C-ITS supports safer, more efficient, and intelligent transport. At the same time, expanded connectivity enlarges the cyberattack surface, exposing safety functions such as braking, steering, and traffic signal control to potential manipulation. This chapter contributes a literature-based conceptual mapping that uses a tri-level perspective to relate vulnerabilities to detection techniques. It pinpoints technical challenges, including false positives, latency, scalability, heterogeneity, and adversarial machine learning, and discusses strategies such as hybrid intrusion detection systems (IDS). To further enhance applicability, it presents methodologies including simulations, hardware-in-the-loop testbeds, and case studies based on C-Roads implementations. It further incorporates cybersecurity asset management and cybersecurity risk assessment as part of the C-ITS ecosystem, consistent with the NIST Cybersecurity Framework (CSF) and ISO/SAE 21434 standard, to enforce regulation and lifecycle-dependent security administration. The chapter also highlights the research challenges, which include asset-agnostic detection, insider and supply-chain threats, adversarial resilience, regulation alignment, and few real-world verifications, and provides a roadmap to further develop IDS research and practice toward C-ITS.