AI-Driven Post-Quantum Cryptography for Cyber-Resilient V2X Communication in Transportation Cyber-Physical Systems
Akid Abrar, Sagar Dasgupta, Mizanur Rahman, Ahmad Alsharif
TL;DR
The work addresses the urgency of quantum-resilient TCPS communications by reviewing PQC algorithm families and their suitability for V2X environments, while highlighting the latency and bandwidth constraints of safety-critical messaging. It argues for AI-driven cryptographic agility to dynamically select, deploy, and manage PQC primitives, enabling threat forecasting, resource optimization, and anomaly detection in real time. By synthesizing PQC standards (Kyber, Dilithium, SPHINCS+) with adaptive AI orchestration, the paper provides a roadmap for deploying quantum-safe TCPS with maintained performance, including concrete considerations for hybrids and field pilots. The practical impact lies in delivering cyber-resilient, scalable, and autonomous TCPS security that can adapt to evolving quantum threats without compromising safety and efficiency.
Abstract
Transportation Cyber-Physical Systems (TCPS) integrate physical elements, such as transportation infrastructure and vehicles, with cyber elements via advanced communication technologies, allowing them to interact seamlessly. This integration enhances the efficiency, safety, and sustainability of transportation systems. TCPS rely heavily on cryptographic security to protect sensitive information transmitted between vehicles, transportation infrastructure, and other entities within the transportation ecosystem, ensuring data integrity, confidentiality, and authenticity. Traditional cryptographic methods have been employed to secure TCPS communications, but the advent of quantum computing presents a significant threat to these existing security measures. Therefore, integrating Post-Quantum Cryptography (PQC) into TCPS is essential to maintain secure and resilient communications. While PQC offers a promising approach to developing cryptographic algorithms resistant to quantum attacks, artificial intelligence (AI) can enhance PQC by optimizing algorithm selection, resource allocation, and adapting to evolving threats in real-time. AI-driven PQC approaches can improve the efficiency and effectiveness of PQC implementations, ensuring robust security without compromising system performance. This chapter introduces TCPS communication protocols, discusses the vulnerabilities of corresponding communications to cyber-attacks, and explores the limitations of existing cryptographic methods in the quantum era. By examining how AI can strengthen PQC solutions, the chapter presents cyber-resilient communication strategies for TCPS.