Community Link Prediction

Links Reconstruction Attack Using Link Prediction Algorithms to Compromise Social Networks Privacy

by Michael Fire

Co-authored with Gilad Katz, Lior Rokach and Yuval Elovici

The explosion in the use of social networks has led to the creation of new kinds of security and privacy threats. Many... more The explosion in the use of social networks has led to the creation of new kinds of security and privacy threats. Many users are unaware of the risks involved with exposing personal information, a fact that makes social networks a “bonanza” for spammers and identity thieves. In addition, it has already been proven that even the concealment of all personal data might not be enough to provide protection, as one’s personal information can be inferred by analyzing one’s connections to other users. In this paper we present the “link reconstruction attack”, a method capable of inferring one’s connections to others with high accuracy. We show that the concealment of ones links is ineffective if not done by others in the network and present an analysis of the performance of various machine learning algorithms for link prediction inside communities.