Privacy preserving social networking

Individual privacy in social networks has become a major concern of late. In spite of adoption of various anonymisation techniques for user profiles, various attacks are possible. Each user needs to be anonymised depending on their sensitivity. Sensitivity can be measured by the relative importance of the user on the basis of degree centrality and prestige rank. This paper proposes various algorithms to automatically generalise the nodes for preserving privacy. Issues like information loss are also discussed.

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