LAPMS: A Lightweight and Privacy-Preserving Management Scheme for Secure Vehicle Platoons

Vehicle platooning, an advanced driving strategy, arranges vehicles into a queue-like formation to reduce fuel consumption and ease road congestion. In platoon management, vehicles are grouped based on attribute similarity, with reliability assessed via reputation values to select appropriate leaders. To address security concerns arising from the potential leakage of sensitive data, such as vehicle attributes and reputation values, we propose a comprehensive privacy-preserving platoon management framework that safeguards privacy throughout the platoon’s lifecycle, from formation to dissolution. Our solution first introduces a secure vehicle attribute matching scheme, which uses scalar product operations to efficiently group vehicles. Reputation ciphertext comparison on the server is enabled by Order Revealing Encryption (ORE) techniques, ensuring the reliable selection of the lead vehicle. Homomorphic encryption further mitigates the security risks of feedback report leakage. Additionally, security analysis indicates that our framework is robust against several common attacks. Simulation results validate its efficiency, demonstrating reduced computational and communication overhead compared to existing solutions.