UM: A Novel Seclusion Model for Defending Structural Information of Social Network Data
Journal Title: International Journal of Research in Computer and Communication Technology - Year 2014, Vol 3, Issue 9
Abstract
Publishing or sharing the social network data for social science research and business analysis lack of privacy. Existing technique k-anonymity is used to prevent identification of micro data. Even though an attacker may gaining sensitive data if a group of nodes largely share the same sensitive labels. We propose an algorithm, universal –match based Indirect Noise Node which makes use of noise nodes to preserve utilities of the original graph. Finally that technique prevents an attacker from reidentifying a user and finding the fact that a certain user has a specific sensitive value.
Authors and Affiliations
N Nalini Krupa, CH. S. V. V. S. N Murty
Keywords
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