针对有向社交网络的Sybil检测方法

doi:10.3969/j.issn.1001-2400.2016.02.034

Abstract

Abstract:

A Sybil detection method based on the random walk strategy is proposed to detect the Sybil nodes in the directed social network. The performance of the algorithm is evaluated by collecting the real social network topological data on Sina Weibo, and the effectiveness of the algorithm is proved. In addition, compared with the existing SybilDefender method, it is found that the false alarm rate of SybilDefender is about 1.6 times as great as SybilGrid. Meanwhile, to achive the same false alarm probability, the random walk length required by SybilGrid is much shorter, meaning that the detection efficiency of SybilGrid is higher.

Key words: Sybil attack, social networks, random walk

WANG Yongcheng;MENG Yanhong. SybilGrid: Sybil detection method based on directed social networks[J].Journal of Xidian University, 2016, 43(2): 199-204.

References

［1］ YU Y, WANG X. World Cup 2014 in the Twitter World: A Big Data Analysis of Sentiments in U.S. Sports Fans' Tweets［J］. Computers in Human Behavior, 2015, 48: 392-400.
［2］ ZHANG L, PENG T Q. Breadth, Depth and Speed: Diffusion of Advertising Messages on Microblogging Sites［J］. Internet Research Electronic Networking Applications ＆ Policy, 2015, 25: 453-470.
［3］ DANEZIS G, MITTAL P. Sybilinfer: Detecting Sybil Nodes Using Social Networks［C］//16th Annual Network ＆ Distributed System Security Symposium. Reston: Internet Society, 2009: 39-53.
［4］ TRAN N, LI J, SUBRAMANIAN L, et al. Optimal Sybil-resilient Node Admission Control［C］//Proceedings of the IEEE International Conference on Computer Communications. Piscataway: IEEE, 2011: 3218-3226.
［5］ NOH G, KANG Y M, OH H, et al. Robust Sybil Attack Defense with Information Level in Online Recommender Systems［J］. Expert Systems with Applications, 2014, 41(4):1781-1791.
［6］ YU H F, GIBBONS P B, KAMINSKY M, et al. SybilLimit: a Near-optimal Social Network Defense Against Sybil Attacks［J］. IEEE/ACM Transactions on Networking, 2010, 18(3): 885-898.
［7］ YU H F, KAMINSKY M, GIBBONS P B, et al. SybilGuard: Defending Against Sybil Attacks via Social Networks［J］. IEEE/ACM Transactions on Networking, 2008, 16(3): 576-589.
［8］ WEI W, XU F, TAN C C, et al. SybilDefender: a Defense Mechanism for Sybil Attacks in Large Social Networks［J］. IEEE Transactions on Parallel ＆ Distributed Systems, 2013, 24(12): 2492-2502.
［9］ LIU P F, WANG X H, CHE X Q, et al. Defense Against Sybil Attacks in Directed Social Networks［C］//Proceedings of the 19th International Conference on Digital Signal Processing. Piscataway: IEEE, 2014: 239-243.
［10］ ERD〃OS P, R'ENYI A. On Random Graphs［J］. Publicationes Mathematicae Debrecen, 1959, 6: 290-297.

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SybilGrid: Sybil detection method based on directed social networks

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