Anonymizing Social Network Using Bipartite Graph

Social networks applications have become popular for sharing information. Social networks data usually contain users´private information. So privacy preservation technologies should be exercised to protect social networks against various privacy leakages and attacks. In this paper, we give an approach for anonymizing social networks which can be represented as bipartite graphs. We propose automorphism publication to protect against multiple structural attacks and develop a BKM algorithm. We perform experiments on bipartite graph data to study the utility and information loss measure.