Skip to Main content Skip to Navigation
Conference papers

Exploiting Trust and Distrust Information to Combat Sybil Attack in Online Social Networks

Abstract : Due to open and anonymous nature, online social networks are particularly vulnerable to the Sybil attack, in which a malicious user can fabricate many dummy identities to attack the systems. Recently, there is a flurry of interests to leverage social network structure for Sybil defense. However, most of graph-based approaches pay little attention to the distrust information, which is an important factor for uncovering more Sybils. In this paper, we propose an unified ranking mechanism by leveraging trust and distrust in social networks against such kind of attacks based on a variant of the PageRank-like model. Specifically, we first use existing topological anti-Sybil algorithms as a subroutine to produce reliable Sybil seeds. To enhance the robustness of these approaches against target attacks, we then also introduce an effective similarity-based graph pruning technique utilizing local structure similarity. Experiments show that our approach outperforms existing competitive methods for Sybil detection in social networks.
Document type :
Conference papers
Complete list of metadata

Cited literature [14 references]  Display  Hide  Download

https://hal.inria.fr/hal-01381680
Contributor : Hal Ifip <>
Submitted on : Friday, October 14, 2016 - 3:19:46 PM
Last modification on : Friday, October 14, 2016 - 3:35:23 PM

File

978-3-662-43813-8_6_Chapter.pd...
Files produced by the author(s)

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Huanhuan Zhang, Chang Xu, Jie Zhang. Exploiting Trust and Distrust Information to Combat Sybil Attack in Online Social Networks. 8th IFIP International Conference on Trust Management (IFIPTM), Jul 2014, Singapore, Singapore. pp.77-92, ⟨10.1007/978-3-662-43813-8_6⟩. ⟨hal-01381680⟩

Share

Metrics

Record views

288

Files downloads

164