A sybil attack detection approach using neighboring vehicles in VANET

Vehicular Ad Hoc Network (VANET) is vulnerable to many security threats. One severe attack is Sybil attack, in which a malicious node forges a large number of fake identities in order to disrupt the proper functioning of VANET applications. In this paper, a distributed and robust approach is presented to defend against Sybil attack. Proposed scheme localizes the fake identities of malicious vehicles by analyzing the consistent similarity in neighborhood information of neighbors of these fake identities. Beacon packets are exchanged periodically by all the vehicles to announce their presence and get aware of neighboring nodes. Each node periodically keep a record of its neighboring nodes. In proposed approach, each node exchange groups of its neighboring nodes periodically and perform the intersection of these groups. If some nodes observe that they have similar neighbors for a significant duration of time, these similar neighbors are identified as Sybil nodes. Proposed approach is able to locate Sybil nodes quickly without the requirement of secret information exchange and special hardware support. We evaluate our proposed approach on the realistic traffic scenario. Experiment results demonstrate that detection rate increases when optimal numbers of Sybil nodes are forged by the attacker.