Preventing Senstive Social Network Data By Using UINN Algorithm

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 microdata. 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.