Edinburgh Napier University

  Decentralized and Connected Autonomous Vehicle (CAV) networks present significant opportunities for improving road safety, efficiency, and traffic management. However, the widespread deployment of these systems is hindered by critical security and privacy challenges, particularly due to the threats posed by quantum computing. In this paper, we propose a robust framework that leverages post-quantum secure zero-knowledge proofs (ZKPs) to enable privacy-preserving authentication and reliable model verification within decentralized CAV networks. Our proposed approach integrates novel lattice-based ZKP protocols, offering quantum-resistant solutions capable of securely authenticating participating vehicles without exposing sensitive identity or location information. Additionally, we introduce a hybrid mechanism combining optimized Binius ZKPs with lattice-based methods, significantly enhancing computational efficiency during model verification processes. To address scalability and efficiency requirements in large-scale CAV infrastructures, we implement a Multi-Layer Compressed Counting Bloom Filter (ML-CCBF) to facilitate lightweight and reliable membership verification. Comprehensive experimental evaluations demonstrate the efficacy of our framework in terms of quantum attack resistance, fault tolerance, computational performance, and scalability. The results indicate that our solution effectively balances security, privacy, and performance, presenting a practical pathway toward resilient, trustworthy, and privacy-centric decentralized CAV networks in the quantum computing era.