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Privacy Preserving Social Network Publication on Bipartite Graphs

  • Jian Zhou
  • Jiwu Jing
  • Ji Xiang
  • Lei Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7322)

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.

Keywords

data publishing privacy preservation bipartite graph generalization 

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Copyright information

© IFIP International Federation for Information Processing 2012

Authors and Affiliations

  • Jian Zhou
    • 1
  • Jiwu Jing
    • 1
  • Ji Xiang
    • 1
  • Lei Wang
    • 1
  1. 1.The State Key Laboratory of Information SecurityGraduate University of Chinese Academy of SciencesChina

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