A group authentication and privacy-preserving level for vehicular networks based on fuzzy system

Vehicular ad hoc networks play an important role in current intelligent transportation networks, which have attracted much attention from academia and industry. Vehicular networks can be implemented by Long-Term Evolution Advanced (LTE-A) networks, which have been formally defined in a series of standards by third-generation partnership projects (3GPP). Abundant challenges exist in the authentication processes in LTE-A-based vehicular networks. This paper aimed to improve the security functionality of these vehicular networks by proposing a secure and efficient group authentication and privacy-preserving scheme for vehicular networks based on fuzzy system: the group authentication and privacy-preserving level (GAPL). Compared with existing schemes, the proposed scheme can greatly reduce the number of control message transmissions from mass vehicular equipment (VEs) to the network and substantially avoid overhead in LTE-A-based vehicular networks. Privacy-preserving levels are established to protect VE privacy in authentication. Furthermore, the scheme contains security functions, including privacy preservation, non-frameability and non-repudiation verification.