Systems Colloquium
Tuesday, March 30, 2010
4:00 p.m., AKW 200

Host: Bryan Ford

Speaker: Nguyen Tran, NYU

Title: Sybil-Resilient Online Content Voting

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 talk, I will 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.

Bio: Nguyen Tran is a PhD candidate at New York University. His research interests lie in distributed systems and networking. His Ph.D. thesis project focuses on creating new primitives to address the security and incentive challenges for large-scale cooperative systems such as online user communities and peer-to-peer systems. Nguyen obtained his undergraduate degree in Computer Science at National University of Singapore before joining NYU.