An Efficient and Multi-Dimensional Privacy-Preserving Platoon Communication Scheme in Vehicular Networks

Vehicular platoon, a cutting-edge technology in the realm of intelligent transportation systems, holds the promise of transforming vehicle operations on roadways. By fostering seamless communication among vehicles and leveraging advanced automation, vehicular platoon enables vehicles to travel closely together, thereby reducing aerodynamic drag, optimizing fuel consumption, and improving road safety. However, due to their open and highly dynamic characteristics, the existing platoon communication schemes face efficiency and privacy challenges. These challenges stem from a substantial overhead on the Trusted Authority (TA) and vehicle sides during platoon communication, and a lack of multi-dimensional privacy preservation (e.g., identity privacy, location privacy, attribute privacy, and reputation value privacy) for platoon vehicles. To overcome these challenges, in this paper, we propose an efficient and multi-dimensional privacy-preserving platoon communication (EMPPC) scheme. Specifically, platoon formation is cloud-assisted and relies on the location, attribute, and reputation value of vehicles. We introduce a secure reputation value ciphertext comparison (SRCC) protocol during platoon leader selection, and present an attribute verification and matching (AVM) algorithm during platoon followers matching. Theoretical analysis and simulation evaluation demonstrate that the EMPPC scheme can offer multi-dimensional privacy preservation, and it is secure and efficient for platoon communication.