Privacy Preserving Social Network Publication on Bipartite Graphs

Abstract : In social networks, some data may come in the form of bipartite graphs, where properties of nodes are public while the associations between two nodes are private and should be protected. When publishing the above data, in order to protect privacy, we propose to adopt the idea generalizing the graphs to super-nodes and super-edges. We investigate the problem of how to preserve utility as much as possible and propose an approach to partition the nodes in the process of generalization. Our approach can give privacy guarantees against both static attacks and dynamic attacks, and at the same time effectively answer aggregate queries on published data.
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Ioannis Askoxylakis; Henrich C. Pöhls; Joachim Posegga. 6th International Workshop on Information Security Theory and Practice (WISTP), Jun 2012, Egham, United Kingdom. Springer, Lecture Notes in Computer Science, LNCS-7322, pp.58-70, 2012, Information Security Theory and Practice. Security, Privacy and Trust in Computing Systems and Ambient Intelligent Ecosystems. 〈10.1007/978-3-642-30955-7_7〉
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Jian Zhou, Jiwu Jing, Ji Xiang, Lei Wang. Privacy Preserving Social Network Publication on Bipartite Graphs. Ioannis Askoxylakis; Henrich C. Pöhls; Joachim Posegga. 6th International Workshop on Information Security Theory and Practice (WISTP), Jun 2012, Egham, United Kingdom. Springer, Lecture Notes in Computer Science, LNCS-7322, pp.58-70, 2012, Information Security Theory and Practice. Security, Privacy and Trust in Computing Systems and Ambient Intelligent Ecosystems. 〈10.1007/978-3-642-30955-7_7〉. 〈hal-01534307〉

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