The Study of Data Publishing Technology based on the Differential Privacy in Social Networks

With the increasing prevalence of social network, research on privacy preserving data publishing in the social network has received substantial attention recently, and the recent emergence of differential privacy has shown great promise for rigorous prevention of information publishing. In this paper, we applied the differential privacy to protect the user information during the data publishing and provided a holistic solution for data publication. In addition, we also explored the influence caused by the query function sensitivity and the privacy preserving budget. The results show that the privacy protection degree increases with the increasing of the privacy preserving budget, while decreases with the increasing of the query function sensitivity.