Vehicular networks: a survey on security, privacy and future challenges

Abstract Vehicular networks (VNs) are playing a key role in shaping the future of intelligent transportation systems by enabling real-time communication among vehicle-to-vehicle, vehicle-to-infrastructure, and broader entities vehicle-to-everything. These networks offer immense potential for improving road safety, easing traffic congestion, and supporting smart mobility services. At the same time, their open and dynamic nature brings significant challenges related to privacy and security, including risks like unauthorized access, data breaches, location tracking, and denial-of-service attacks. This survey offers a comprehensive overview of the major security and privacy concerns confronted by the contemporary VNs. It introduces a clear taxonomy that organizes various threat categories, defense strategies, and cryptographic techniques that are commonly used in this domain. Recent developments are reviewed and grouped based on various authentication schemes, blockchain-based methods, privacy-preserving protocols, and artificial intelligence-driven intrusion detection systems. These solutions are then evaluated in terms of their cryptographic robustness, privacy safeguards, processing requirements, and their suitability for fitting into real-world applications such as autonomous driving and vehicular edge computing. Beyond the current landscape, the paper also outlines key gaps and promising research directions, including federated learning, lightweight blockchain consensus mechanisms, quantum-resistant cryptography, and intelligent threat detection at the edge. By bringing together both foundational concepts and the latest innovations, this survey aims to support researchers and practitioners in understanding the contemporary security challenges inherent to the VNs and building more secure, scalable, and privacy-aware vehicular communication systems.