Footprint: Detecting Sybil Attacks in Urban Vehicular Networks
In urban vehicular networks, where privacy, especially the location privacy of anonymous vehicles is highly concerned, anonymous verification of vehicles is indispensable. Consequently, an attacker who succeeds in forging multiple hostile identifies can easily launch a Sybil attack, gaining a disproportionately large influence. In this paper, the authors propose a novel Sybil attack detection mechanism, Footprint, using the trajectories of vehicles for identification while still preserving their location privacy. More specifically, when a vehicle approaches a Road-Side Unit (RSU), it actively demands an authorized message from the RSU as the proof of the appearance time at this RSU.