Vehicular platooning demands secure and trustworthy inter-vehicle communications to maintain platoon stability, traffic efficiency, and driving safety. Existing privacy-preserving authentication schemes protect message integrity over open channels but often overlook the credibility of message content, allowing authenticated yet misleading data. Reputation management frameworks address this by evaluating vehicle behavior, yet most employ periodic updates, delaying detection of sudden misbehavior. This paper proposes a reputation-based authentication mechanism (EPRU) that establishes trust between vehicles by evaluating vehicle behavior and historical records, thereby ensuring the reliability of message transmission between vehicles. Our EPRU incorporates a dynamic aggregation trigger mechanism that updates vehicle credit scores based on verified feedback collected in real time, thereby accurately reflecting behavioral changes. Furthermore, a combination of ElGamal encryption and homomorphic encryption is employed to safeguard vehicle identities and feedback data during transmission and processing. Formal security proofs and extensive analysis demonstrate resistance to forgery, replay, and modification attacks, ensuring the confidentiality, integrity, and authenticity of both messages and feedback data. Experimental results demonstrate that our EPRU reduces computation overhead by at least 3.05% and communicational cost by 37.5% compared with recent state-of-the-art schemes, highlighting its practicality and efficiency for real-time, privacy-aware vehicular platoon systems.

Vehicular platooning has emerged as a promising paradigm in intelligent transportation, offering significant benefits such as reduced energy consumption, improved road throughput and mitigated traffic congestion. However, the open nature of vehicular communication channels exposes platoons to a wide range of security and privacy threats. Although existing group key-based protocols provide foundational security services, they often incur substantial computation overhead and insufficiently address vehicle privacy, making them unsuitable for dynamic vehicular platoon. Therefore, this paper introduces an efficient group authentication protocol (EEGAP) for dynamic vehicular platoons, which ensures privacy-preserving and secure communication during platoon restructuring operations, such as merging and splitting, by integrating anonymous authentication, fog computing, and group key agreement mechanisms. Leveraging Elliptic Curve Cryptography (ECC) and secret sharing mechanisms, EEGAP enables lightweight yet robust group key negotiation, reducing computation overhead by 7.08% and communication overhead by 6.85% compared to existing schemes. Both formal security proofs and informal analysis confirm that EEGAP satisfies the stringent security requirements of vehicular platoon communication systems.

The vehicular ad hoc network (VANET) is a platform for exchanging information between vehicles and everything to enhance driver’s driving experience and improve traffic conditions. The reputation system plays an essential role in judging whether to communicate with the target vehicle based on other vehicles’ feedback. However, existing reputation systems ignore the privacy protection of feedback providers. Additionally, traditional VANET based on wireless sensor networks (WSNs) has limited power, storage, and processing capabilities, which cannot meet the real-world demands in a practical VANET deployment. Thus, we attempt to integrate cloud computing with VANET and proposes a privacy-preserving protocol of vehicle feedback (PPVF) for cloud-assisted VANET. In cloud-assisted VANET, we integrate homomorphic encryption and data aggregation technology to design the scheme PPVF, in which with the assistance of the roadside units (RSU), cloud service provider (CSP) obtains the total number of vehicles with the corresponding parameters in the feedback for reputation calculation without violating individual feedback privacy. Simulation results and security analysis confirm that PPVF achieves effective privacy protection for vehicle feedback with acceptable computational and communication burden. Besides, the RSU is capable of handling 1999 messages for every$300ms$, so as the number of vehicles in the communication domain increases, the PPVF has a lower message loss rate.