Reinforcement learning based group key agreement scheme with reduced latency for VANET

Abstract

Key agreement scheme of vehicle ad hoc networks (VANET) determines the privacy and security against user identity-based attacks,such as spoofing attack.The existing work updates the group shared key at a fixed frequency,which increases the processing latency of the key updates and the encryption and decryption of group communication.A reinforcement learning based dynamic key agreement scheme was proposed to enable the group cluster head to optimize the key update frequency and key length.This scheme optimizes the calculation latency of encryption and decryption based on the number of surrounding vehicles,the previous key update records without the knowledge of the traffic flow model and the access-driven cache attack model.Simulation results show that this scheme reduces the transmission delay of the communication overhead and the computational latency of encryption and decryption,and improves the security of the group key compared with the benchmark scheme.

Keywords

• VANET;group key agreement;reinforcement learning