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2009
ACM

On Link Privacy in Randomizing Social Networks

12 years 2 months ago
On Link Privacy in Randomizing Social Networks
Many applications of social networks require relationship anonymity due to the sensitive, stigmatizing, or confidential nature of relationship. Recent work showed that the simple technique of anonymizing graphs by replacing the identifying information of the nodes with random ids does not guarantee privacy since the identification of the nodes can be seriously jeopardized by applying subgraph queries. In this paper, we investigate how well an edge based graph randomization approach can protect sensitive links. We show via theoretical studies and empirical evaluations that various similarity measures can be exploited by attackers to significantly improve their confidence and accuracy of predicted sensitive links between nodes with high similarity values.
Xiaowei Ying, Xintao Wu
Added 20 May 2010
Updated 20 May 2010
Type Conference
Year 2009
Where PAKDD
Authors Xiaowei Ying, Xintao Wu
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