Cybersecurity threats mitigation in Internet of Vehicles communication system using reliable clustering and routing

Abstract

Security and privacy while considering vehicular networks are important research topics. Appropriate clustering algorithms enable long-distance communications in highly dynamic Internet of Vehicles (IoV) systems. IoV system QoS requires constant, low-cost clustering. However, to prevent malicious behaviors, sensitive vehicle networks need an access control system for data security and privacy. The existing solutions suffered from higher complexity and complete reliability. Thus, the main objective of this paper is to propose a lightweight routing technique to express network access control policies to ensure higher reliability with minimum latency and overhead. The Trust Aware Clustering-based Routing Protocol (TACR) solves IoV communication security and reliability issues while reducing computational costs and latency. TACR functionality relies on trust-management methods for optimal Cluster Head (CH) and relay (data forwarder) selection. Each car's direct and indirect trust scores are calculated during clustering. The fitness function of the Ant Colony Optimisation (ACO) algorithm uses each vehicle's hybrid trust value. The ACO algorithm chooses stable vehicles for the best CH. In the routing phase, we select forwarding relays and apply trust-based access control rules to ensure safe and reliable data transmission. Fuzzy logic selects the optimal relay node and sets access control rules based on trust evaluation. The trust criteria consider each vehicle's expertise, knowledge, and suggestions throughout. The simulation findings reveal that the TACR protocol outperforms state-of-the-art protocols significantly. Average throughput and PDR are increased by 14.17 % and 14.34 % using TACR, respectively. Average delay and communication overhead were reduced by 33.84 % and 14.28 % using the TACR protocol, respectively.