Defense against sybil attacks in directed social networks

In this paper, we attempt to solve the problem of defense against sybil attacks in directed social networks. We propose a set of measures for the quality of network partitions, with modularity as a special case. We present an algorithm based on the set of measures and iterative optimization to detec...

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Bibliographic Details
Main Authors: Pengfei Liu, Xiaohan Wang, Xiangqian Che, Zhaoqun Chen, Yuantao Gu
Format: Conference Proceeding
Language:English
Subjects:
Atomic measurements
Communities
Detection algorithms
Digital signal processing
directed networks
modularity
Partitioning algorithms
security
set of measures
Signal processing algorithms
Social network services
social networks
spam
sybil attack
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Summary:In this paper, we attempt to solve the problem of defense against sybil attacks in directed social networks. We propose a set of measures for the quality of network partitions, with modularity as a special case. We present an algorithm based on the set of measures and iterative optimization to detect the sybil region. The algorithm is evaluated using a subset of real-world social topology and is confirmed to be efficient for solving the problem. Moreover, a comparison between the proposed algorithm and SybilDefender is provided, which shows that the proposed algorithm is superior for the sybil region detection problem in directed social networks.
ISSN:1546-1874
2165-3577
DOI:10.1109/ICDSP.2014.6900836