An adaptive and secure traffic information forwarding mechanism in Internet of Vehicles

Traffic information of disparate types in Internet of Vehicles (IoV) is the basis for supporting various IoV applications. Since traffic flows vary in real time, it is challenging to carry out efficient and reliable transfer of such information. Moreover, IoV is vulnerable to security threats due to its inherent properties such as dynamically changing topology and high-speed motion of vehicles. Attacks, once launched successfully, would also disrupt message transmission between vehicles. We propose an adaptive traffic information forwarding mechanism, which divides traffic information in two categories, that is, early warning information and service information. The former is handled by selecting a relay node based on node connection stability evaluation, while the latter is handled by adopting an appropriate forwarding method according to the identified traffic flow density. Specifically, in a low-density environment, we employ a broadcast method; while in a high-density environment, we evaluate the cognitive interaction values of vehicle nodes and employ a cognitive interaction-based method to select a relay node. Simulation results show that the proposed mechanism improves the forwarding efficiency of traffic information and yields satisfactory performance in mitigating black hole attacks.