IPTPS '01 Revised Papers from the First International Workshop on Peer-to-Peer Systems
The sybil attack in sensor networks: analysis & defenses
Proceedings of the 3rd international symposium on Information processing in sensor networks
The Security and Privacy of Smart Vehicles
IEEE Security and Privacy
Detecting and correcting malicious data in VANETs
Proceedings of the 1st ACM international workshop on Vehicular ad hoc networks
An RSSI-based Scheme for Sybil Attack Detection in Wireless Sensor Networks
WOWMOM '06 Proceedings of the 2006 International Symposium on on World of Wireless, Mobile and Multimedia Networks
Detection and localization of sybil nodes in VANETs
DIWANS '06 Proceedings of the 2006 workshop on Dependability issues in wireless ad hoc networks and sensor networks
Securing vehicular ad hoc networks
Journal of Computer Security - Special Issue on Security of Ad-hoc and Sensor Networks
SybilGuard: defending against sybil attacks via social networks
IEEE/ACM Transactions on Networking (TON)
Privacy-Preserving Detection of Sybil Attacks in Vehicular Ad Hoc Networks
MOBIQUITOUS '07 Proceedings of the 2007 Fourth Annual International Conference on Mobile and Ubiquitous Systems: Networking&Services (MobiQuitous)
A Robust Detection of the Sybil Attack in Urban VANETs
ICDCSW '09 Proceedings of the 2009 29th IEEE International Conference on Distributed Computing Systems Workshops
Using TPMs to secure vehicular ad-hoc networks (VANETs)
WISTP'08 Proceedings of the 2nd IFIP WG 11.2 international conference on Information security theory and practices: smart devices, convergence and next generation networks
Defense against Sybil attack in vehicular ad hoc network based on roadside unit support
MILCOM'09 Proceedings of the 28th IEEE conference on Military communications
SECURING VEHICULAR COMMUNICATIONS
IEEE Wireless Communications
A sybil attack detection approach using neighboring vehicles in VANET
Proceedings of the 4th international conference on Security of information and networks
Misbehavior detection based on ensemble learning in VANET
ADCONS'11 Proceedings of the 2011 international conference on Advanced Computing, Networking and Security
Privacy representation in VANET
Proceedings of the third ACM international symposium on Design and analysis of intelligent vehicular networks and applications
Prevention of DoS Attacks in VANET
Wireless Personal Communications: An International Journal
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Security is an important concern for many Vehicular Ad hoc Network (VANET) applications. One particular serious attack, known as Sybil attack, against ad hoc networks involves an attacker illegitimately claiming multiple identities. In this paper, we present a simple security scheme, based on the difference in movement patterns of Sybil nodes and normal nodes, for detecting Sybil nodes in VANET. Our approach is distributed in nature because all nodes contribute for detection of Sybil nodes in VANET and it scales well in an expanding network. In this approach, each Road Side Unit (RSU) calculates and stores different parameter values (Received Signal Strength, distance, angle) after receiving the beacon packets from nearby vehicles. The reason for choosing the angle as one of the parameters is that it will always be different for two vehicles (not moving side-by-side), even if they have same values for distance and received signal strength (RSS) with reference to a RSU. The combination of the parameters makes our detection approach highly accurate. After a significant observation period, these RSUs exchange their records and calculate the difference of the parameters. If some nodes have same values for the parameters during this observation period, these nodes are classified as Sybil nodes. Our preliminary simulation results show 99% accuracy and approximately 0.5% error rate, lower as compared to existing techniques.