Detection of malicious vehicles (DMV) through monitoring in Vehicular Ad-Hoc Networks

Vehicular Ad Hoc Networks (VANETs) are appropriate networks that can be applied to intelligent transportation systems. In VANET, messages exchanged among vehicles may be damaged by attacker nodes. Therefore, security in message forwarding is an important factor. We propose the Detection of Malicious Vehicles (DMV) algorithm through monitoring to detect malicious nodes that drop or duplicate received packets and to isolate them from honest vehicles, where each vehicle is monitored by some of it trustier neighbors called verifier nodes. If a verifier vehicle observes an abnormal behavior from vehicle V, it increases distrust value of vehicle V. The ID of vehicle V is then reported to its relevant Certificate Authority (CA) as a malicious node when its distrust value is higher than a threshold value. Performance evaluation shows that DMV can detect most existence abnormal and malicious vehicles even at high speeds.