Robust Sybil Attack Detection in Vehicular Networks

The broadcast nature of the vehicular networks makes them vulnerable to Sybil attacks, where an attacker illegitimately claims multiple identities and undermines the networks. We propose a non-cryptographic attack detection approach that is based on signal-level wireless measurements. Our approach exploits the spatial signal variation of wireless channels to detect Sybil attacks. The performance of our approach is verified via extensive simulations and DSRC-based experiments in a real vehicular network. The results show that we achieve the detection rates of 95% in simulations and 99% in real-world experiments. The proposed approach can be deployed on the existing systems without a need for additional hardware or infrastructure.