RSSI-Based Sybil Attack Detection Under Fading Channel in VANET

Sybil attack is one of the most serious attacks in vehicular ad hoc network (VANET), where a malicious node forges many illegal identities to interfere with or even control the network, which brings severe security threats to the intelligent transportation system. Received signal strength indicator (RSSI) is highly relative to the positions of communication nodes, and can be applied for sybil attack detection according to the fact that two real nodes cannot be in the same position. However, the high mobility of nodes in VANET makes it more difficult to be applied directly. In this paper, an improved RSSI-based sybil attack detection method is proposed against the fading channel and the high mobility of nodes in VANET. This method first estimates the distance between each communication node through maximum likelihood estimation, and then detects sybil nodes through mean-shift clustering algorithm. The numerical simulation results show the propose sybil attack detection has high accuracy in VANET by appropriately setting the detection time and the searching radius of the mean-shift algorithm.