Sybil defenses in mobile social networks

Mobile social networks are vulnerable to Sybil attacks. By creating a large number of fake identities, malicious users can gain a disproportionately high benefit through a Byzantine fashion. Most social network-based Sybil defenses adopt the assumptions that the honest region is a fast-mixing network. However, more and more evidence shows that some real social networks are not fast-mixing, especially when only strong-trust relations are considered. Moreover, the accuracy of all existing solutions is related to the number of attack edges that the adversary can build. In this paper, for addressing these problems, we propose a local ranking system for estimating trust-level between users. Our scheme has three unique features. First, our system is based on both trust and distrust relations. Second, instead of storing the entire social graph, users carry limited information related to themselves. Last but not least, our system weakens the impacts of attack edges by removing several suspicious edges with high centrality. We validate the effectiveness of our solutions through comprehensive experiments.