SybilInfer: Detecting Sybil Nodes using Social Networks

George Danezis, Prateek Mittal

Research output: Contribution to conferencePaperpeer-review

301 Scopus citations

Abstract

SybilInfer is an algorithm for labelling nodes in a social network as honest users or Sybils controlled by an adversary. At the heart of SybilInfer lies a probabilistic model of honest social networks, and an inference engine that returns potential regions of dishonest nodes. The Bayesian inference approach to Sybil detection comes with the advantage label has an assigned probability, indicating its degree of certainty. We prove through analytical results as well as experiments on simulated and real-world network topologies that, given standard constraints on the adversary, SybilInfer is secure, in that it successfully distinguishes between honest and dishonest nodes and is not susceptible to manipulation by the adversary. Furthermore, our results show that SybilInfer outperforms state of the art algorithms, both in being more widely applicable, as well as providing vastly more accurate results.

Original languageEnglish (US)
StatePublished - 2009
Externally publishedYes
Event16th Symposium on Network and Distributed System Security, NDSS 2009 - San Diego, United States
Duration: Feb 8 2009Feb 11 2009

Conference

Conference16th Symposium on Network and Distributed System Security, NDSS 2009
Country/TerritoryUnited States
CitySan Diego
Period2/8/092/11/09

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Control and Systems Engineering
  • Safety, Risk, Reliability and Quality

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