CYBERSECURITY THREATS IN INTELLIGENT TRANSPORT SYSTEMS: CHALLENGES AND SOLUTION PATHWAYS
TL;DR
Proposed solutions include integrating international standards, such as ISO/SAE 21434 and the NIST Cybersecurity Framework; applying cryptographic protection to V2X communications; implementing hybrid intrusion detection systems; and adopting lifecycle-oriented risk management across ITS infrastructures.
Abstract
The rapid integration of Intelligent Transport Systems (ITS) into urban and interurban mobility has significantly improved efficiency, safety, and automation in transport operations. Nevertheless, the extensive connectivity enabled by vehicle-to-everything (V2X) communications, Internet of Things (IoT) devices, and cloud services has also increased exposure to cyber threats. The primary scientific challenge is that compromising Cooperative ITS (C-ITS) can enable manipulation of critical transport functions, such as automated control, braking, and signaling, through falsified or maliciously injected communication messages. The increasing frequency of distributed denial-of-service (DDoS) attacks exacerbates this vulnerability, as these attacks account for most publicly recorded incidents worldwide and directly affect the transportation sector. Furthermore, ransomware and supply-chain attacks have led to a marked increase in system breaches and significant financial losses. IoT devices widely deployed within ITS often use inadequately secured communication protocols, creating opportunities for remote intrusion and infrastructure compromise. Simultaneously, Artificial Intelligence (AI) functions as a dual-use technology, facilitating both cyber-attacks, such as automated phishing, adaptive threat generation, and vulnerability analysis, and defense through the deployment of anomaly detection models. Additional risk arises from adversarial attacks that can mislead AI models in autonomous vehicles, thereby undermining real-time decision-making processes. Proposed solutions include integrating international standards, such as ISO/SAE 21434 and the NIST Cybersecurity Framework; applying cryptographic protection to V2X communications; implementing hybrid intrusion detection systems; and adopting lifecycle-oriented risk management across ITS infrastructures. AI-based predictive analytics and anomaly detection are identified as critical approaches to enhancing cyber resilience. Ongoing coordination among operators, vendors, and public institutions is essential to mitigate systemic risks and protect the integrity of ITS environments.