Abstract
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.
Highlights
Under the facilitation of 5G/B5G, bulks of smartapparatuses are connected to the Internet to execute massive information interactions, symbolizing the official arrival of Internet of Things (IoT) [1]
Vehicles can predict the driving direction so that the trust value of the vehicle can be shared point-to-point between Roadside units (RSUs) to conquer the negative impact of the central controller, which brings the benefits as follows: (1) The path prediction algorithm is executed at the vehicle layer to improve network scalability and adapted to Internet of Vehicle (IoV)
This paper proposed an efficient Random Forest (RF)-based trust management mechanism MTRF tailored to the urban scenarios in IoV
Summary
Under the facilitation of 5G/B5G, bulks of smartapparatuses are connected to the Internet to execute massive information interactions, symbolizing the official arrival of Internet of Things (IoT) [1]. It faces a single point of failure problem. Our article proposes a Random Forest-based trust management mechanism named MTRF for IoV to determine vehicles’ identities and ensure vehicle network security. We set a penalty factor to prevent sudden attacks from malicious nodes with higher accumulated trustworthiness (iii) To secure communication links between ClusterMember-vehicles (CMVs), Cluster-Head-Vehicles (CHVs), and RSUs, we introduce a lightweight cryptography scheme based on Elliptic Curve Cryptography (ECC), Cryptographic Hash Function, and, XOR operations (iv) To accurately share the trust information of vehicles during cluster-switching, we propose a trust-sharing mechanism by utilizing a DQN-based path prediction algorithm.
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