Detecting Sybil attacks in VANETs

Bo Yu, Cheng Zhong Xu, Bin Xiao

Research output: Journal article publicationJournal articleAcademic researchpeer-review

116 Citations (Scopus)

Abstract

Sybil attacks have been regarded as a serious security threat to Ad hoc Networks and Sensor Networks. They may also impair the potential applications in Vehicular Ad hoc Networks (VANETs) by creating an illusion of traffic congestion. In this paper, we make various attempts to explore the feasibility of detecting Sybil attacks by analyzing signal strength distribution. First, we propose a cooperative method to verify the positions of potential Sybil nodes. We use a Random Sample Consensus (RANSAC)-based algorithm to make this cooperative method more robust against outlier data fabricated by Sybil nodes. However, several inherent drawbacks of this cooperative method prompt us to explore additional approaches. We introduce a statistical method and design a system which is able to verify where a vehicle comes from. The system is termed the Presence Evidence System (PES). With PES, we are able to enhance the detection accuracy using statistical analysis over an observation period. Finally, based on realistic US maps and traffic models, we conducted simulations to evaluate the feasibility and efficiency of our methods. Our scheme proves to be an economical approach to suppressing Sybil attacks without extra support from specific positioning hardware.
Original languageEnglish
Pages (from-to)746-756
Number of pages11
JournalJournal of Parallel and Distributed Computing
Volume73
Issue number6
DOIs
Publication statusPublished - 25 Mar 2013

Keywords

  • Position verification
  • Sybil attacks
  • VANET

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence

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