A two-stage approach for malicious vehicle detection in vehicular Ad Hoc network.

Vehicle ad hoc networks (VANETs) are small, local networks that could be joined by malicious users, opening the door to a variety of active and passive attacks. This technology creates a wide-area network by connecting automobiles within a range of roughly 100 to 300 meters. The current situation allows for the development of fresh applications that were previously impractical due to the enormous increase in the number of cars outfitted with computing and wireless communication gear. These applications include toll calculation, real-time traffic monitoring, dynamic route configuration, emergency message transmission, data retrieval, and collaborative travel promotion. Traditional vehicle networks relied on a structure that sent data to a central database regarding breakdowns and traffic jams. Instead of relying on a centralized network, VANET enables direct vehicle-to-vehicle communication. Instead of depending on a central monitoring station, VANET enables direct vehicle-to-vehicle communication, which creates opportunities for malicious traffic. Establishing an Intelligent Transport System (ITS) is the main goal of VANET, with security-related applications being a major focus of vehicle-to-vehicle communication. A malicious node present in the network can actively invade the system by causing denial of service. A novel two-phase methodology for the identification and investigation of such attacks is introduced in this study. The methodology's first stage examines suspected harmful nodes, while the second stage uses promiscuous mode to determine whether a node is actually malicious. Using NS2, the proposed technique is simulated, and particular metrics are taken into account to assess the results. [ABSTRACT FROM AUTHOR]