ARPVP: Attack Resilient Position-Based VANET Protocol Using Ant Colony Optimization

The position-based routing of Vehicular Ad hoc Network (VANET) vulnerable to various security attacks because dependency on computing, control, and communication technologies. Internet Things (IoT)-enabled VANET application leads the challenges such as integrity, access availability, privacy protection, non-repudiation, confidentiality. Several solutions have been introduced for two decades in categories cryptography-based trust-based. Due high computation complexity, are outperformed by recent intelligent trust-based mechanisms. techniques lightweight effective against well-known threats VANET. objective this paper has design a novel which conduct vehicles assessed accomplish reliable communications. Attack Resilient Position-based Protocol (ARPVP) proposed detect prevent malicious network using trust evaluation technique artificial intelligence (AI). In first phase ARPVP, periodic self-trust assessment algorithm designed parameters unreliable network. second route formation AI Ant Colony Optimization (ACO). ACO solves problem neglecting attacker's fitness function. each vehicle mobility, buffer occupancy, link quality had measured both phases ARPVP. Simulation outcomes model state-of-art protocols terms average throughput, delay, overhead, Packet Delivery Ratio (PDR).