Online Link Disclosure Strategies for Social Networks

Abstract

While online social networks have become an important channel for social interactions, they also raise ethical and privacy issues. A well known fact is that social networks leak information, that may be sensitive, about users. However, performing accurate real world online privacy attacks in a reasonable time frame remains a challenging task. In this paper we address the problem of rapidly disclosing many friendship links using only legitimate queries (i.e., queries and tools provided by the targeted social network). Our study sheds new light on the intrinsic relation between communities (usually represented as groups) and friendships between individuals. To develop an efficient attack we analyzed group distributions, densities and visibility parameters from a large sample of a social network. By effectively exploring the target group network, our proposed algorithm is able to perform friendship and mutual-friend attacks along a strategy that minimizes the number of queries. The results of attacks performed on active Facebook profiles show that 5 different friendship links are disclosed in average for each single legitimate query in the best case.

This work is funded by Fondation MAIF.