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Internet of Vehicles (IoV) is a novel technology to enhance the safety, intelligence, and efficiency of traffic systems, where vehicles can exchange critical information with other vehicles, roadside units, pedestrians, and cloud platforms. However, the dynamic network topology, high speed, and exposed communication links inevitably pose security threats to IoV. It is pivotal to establish a trust management and trust-sharing mechanism between vehicles to guarantee the safety of IoV. This paper proposes a distributed trust management scheme to discriminate malicious vehicles utilizing the machine learning technology Random Forest (RF). With the help of the sliding time window technology, the trust degree of vehicles can be comprehensively evaluated through the CART trees according to the current and historical records. To further improve the security of communication processes, we also introduce a lightweight cryptography mechanism. In addition, a trust-sharing mechanism based on path prediction algorithm is proposed to guarantee the consistency of trust information in the network. Finally, extensive simulations are conducted to demonstrate the feasibility and efficiency of the proposed scheme.

Joint Trust Management and Sharing Provisioning in IoV-Based Urban Road Network