Title
Votetrust: Leveraging Friend Invitation Graph To Defend Against Social Network Sybils
Abstract
Online social networks (OSNs) currently face a significant challenge by the existence and continuous creation of fake user accounts (Sybils), which can undermine the quality of social network service by introducing spam and manipulating online rating. Recently, there has been much excitement in the research community over exploiting social network structure to detect Sybils. However, they rely on the assumption that Sybils form a tight-knit community, which may not hold in real OSNs. In this paper, we present VoteTrust, a Sybil detection system that further leverages user interactions of initiating and accepting links. VoteTrust uses the techniques of trust-based vote assignment and global vote aggregation to evaluate the probability that the user is a Sybil. Using detailed evaluation on real social network (Renren), we show VoteTrust's ability to prevent Sybils gathering victims (e. g., spam audience) by sending a large amount of unsolicited friend requests and befriending many normal users, and demonstrate it can significantly outperform traditional ranking systems (such as TrustRank or BadRank) in Sybil detection.
Year
DOI
Venue
2013
10.1109/INFCOM.2013.6567045
2013 PROCEEDINGS IEEE INFOCOM
Keywords
Field
DocType
security,graph theory,upper bound,mathematical model,trusted computing
Graph theory,Graph,World Wide Web,Trusted Computing,Social network,Ranking,Computer science,TrustRank,Computer security,Computer network,Social network service
Conference
Volume
Issue
ISSN
null
null
0743-166X
Citations 
PageRank 
References 
20
0.71
19
Authors
6
Name
Order
Citations
PageRank
Jilong Xue1746.27
Zhi Yang237141.32
Xiaoyong Yang3200.71
Xiao Wang4201.05
Lijiang Chen530423.22
Yafei Dai6103567.19