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	An Enhanced Structure-Based De-anonymization of Online Social Networks
	Li, Hong ; Zhang, Cheng ; He, Yunhua ; Cheng, Xiuzhen ; Liu, Yan ; Sun, Limin
	2016
关键词	Social network De-anonymization Network structure PRIVACY SYSTEMS
英文摘要	To protect users' privacy, online social network data are usually anonymized before being sold to or shared with third parities. Various structure-based approaches have been proposed to de-anonymize the social network data. In this paper, we study the limitations of the existing structure-based de-anonymization methods and propose an enhanced de-anonymization algorithm. The basic idea of our algorithm is to leverage the structural transformations of the social graph to de-anonymize the social network data. We also define a new similarity measure that is more robust for de-anonymization. We use the arXiv dataset to evaluate our algorithm, and the experiment results show that our method can significantly improve the de-anonymization rate.; EI; CPCI-S(ISTP); sunlimin@iie.ac.cn; 331-342; 9798
语种	英语
出处	11th International Conference on Wireless Algorithms, Systems and Applications (WASA)
DOI标识	10.1007/978-3-319-42836-9_30
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/449565]
专题	软件与微电子学院
推荐引用方式 GB/T 7714	Li, Hong,Zhang, Cheng,He, Yunhua,et al. An Enhanced Structure-Based De-anonymization of Online Social Networks. 2016-01-01.

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