Spatio-Temporal Analysis Based Resist Conspiracy Sybil Attack Detection in VANETs

In Vehicular Ad Hoc Networks(VANETs), Attacker can obtain multiple network identities by forging, stealing and conspiring with other legal vehicles, then they use these Sybil identities to transmit fake traffic information to create an illusion traffic congestion, even would cause more serious traffic accidents. The most current Sybil attack detection scheme primarily detects forged identity and stolen identity Sybil attack, there is rare research to detect conspiracy Sybil attack. In addition, Sybil attack detection need to bind each vehicle to a single identity in order to keep adversaries from playing multiple roles or spoofing with other legitimate identities, this will lead to privacy reveal issues. In order to balanced solve the two conflicting problems between Sybil attack detection and privacy protection, we propose a resist conspiracy Sybil attack detection method based on Spatio-Temporal Analysis based Resist Conspiracy Sybil Attack(STARCS). The method uses anonymous road side unit(RSU) released timestamp token as identity in VANETs, and there set a table to record RSU that last passed and timestamp by Trust Authority(TA), the table is called request information table to record the RSU and timestamp which vehicle last passed, to defend the generation of stolen and conspired Sybil identities. In this paper, each alarm event only allows each vehicle to release an alert message with timestamp token to detect Sybil attack, and we check whether the timestamp token contained in multiple alert messages and used by a plurality of vehicles at the same time to detect conspiracy Sybil attack which attacker and conspired vehicles using the same identity at the same time, and based on the adjacent relation tag of RSUs which embedded in the timestamp token to detect conspiracy Sybil attack which attacker conspired with the long-distance vehicles launch Sybil attack. Due to we detect conspiracy Sybil attack from the perspective of time to analyze whether the identity is abused or not and from the perspective of spatial to analyze whether the identity is appearing unreasonable displacement or not, that is, from the spatio-temporal analysis to resist and detect conspiracy Sybil attack. Theoretical analysis and simulation results show this method not only can defend or detect various types of Sybil attack, but also has less computation overhead and communication overhead, and it can protect the privacy of vehicle's identity and position by dynamic anonymity mechanism. © 2018, Science Press. All right reserved.