Sybil-resilient online content voting

Nguyen Tran, Bonan Min, Jinyang Li, Lakshminarayanan Subramanian

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Obtaining user opinion (using votes) is essential to ranking user-generated online content. However, any content voting system is susceptible to the Sybil attack where adversaries can out-vote real users by creating many Sybil identities. In this paper, we present SumUp, a Sybil-resilient vote aggregation system that leverages the trust network among users to defend against Sybil attacks. SumUp uses the technique of adaptive vote flow aggregation to limit the number of bogus votes cast by adversaries to no more than the number of attack edges in the trust network (with high probability). Using user feedback on votes, SumUp further restricts the voting power of adversaries who continuously misbehave to below the number of their attack edges. Using detailed evaluation of several existing social networks (YouTube, Flickr), we show SumUp's ability to handle Sybil attacks. By applying SumUp on the voting trace of Digg, a popular news voting site, we have found strong evidence of attack on many articles marked “popular” by Digg.

Original languageEnglish (US)
Title of host publicationProceedings of the 6th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2009
PublisherUSENIX Association
Pages15-28
Number of pages14
ISBN (Electronic)9781931971676
StatePublished - Jan 1 2019
Event6th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2009 - Boston, United States
Duration: Apr 22 2009Apr 24 2009

Publication series

NameProceedings of the 6th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2009

Conference

Conference6th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2009
CountryUnited States
CityBoston
Period4/22/094/24/09

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Control and Systems Engineering

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