Title: CPPABK: conditional privacy-preserving authentication scheme for VANETs based on the key derivation algorithm
Authors: Yixuan Wang; Xian Guo
Addresses: School of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050, China ' School of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050, China
Abstract: Vehicular ad hoc networks (VANETs) hold great potential for enhancing traffic management and driver safety. Consequently, ensuring the precision and reliability of information exchanged within VANETs is paramount. This paper introduces a distributed privacy-preserving authentication scheme explicitly designed for VANETs. Our scheme integrates blockchain technology, batch authentication, and the key derivation algorithm to achieve exceptional efficiency and scalability. Initially, the authentication process utilises fuzzy biometric extraction technology as the fundamental module to authenticate the vehicle owner's identity. Subsequently, the scheme enables vehicles to authenticate the received message by retrieving data (anonymous public key) from the blockchain, thereby mitigating the adverse effects of the blockchain's low throughput and high latency and eliminating the key escrow problem. A comprehensive security analysis confirms that the proposed scheme satisfies the security requirements of VANETs. Furthermore, performance analysis reveals significant improvements across various aspects. Specifically, our scheme achieves reductions in computation cost of up to 66.74% in the signature generation, up to 59.59% in single message verification time, and up to 78.97% in communication cost compared to the comparison schemes.
Keywords: VANETs; blockchain; conditional privacy-preserving authentication; CPPA; key derivation algorithm.
International Journal of Security and Networks, 2023 Vol.18 No.4, pp.199 - 212
Received: 12 Jun 2023
Accepted: 15 Jun 2023
Published online: 15 Dec 2023 *