摘要
There are growing concerns surrounding the data security of social networks because large amount of user information and sensitive data are collected. Differential privacy is an effective method for privacy protection that can provide rigorous and quantitative protection. Concerning the application of differential privacy in social networks,this paper analyzes current trends of research and provides some background information including privacy protection standards and noise mechanisms.Focusing on the privacy protection of social network data publishing,a graph-publishing model is designed to provide differential privacy in social networks via three steps: Firstly,according to the features of social network where two nodes that possess certain common properties are associated with a higher probability,a raw graph is divided into several disconnected sub-graphs,and correspondingly dense adjacent matrixes and the number of bridges are obtained. Secondly,taking the advantage of quad-trees,dense region exploration of the adjacent matrixes is conducted. Finally,using an exponential mechanism and leaf nodes of quad-trees,an adjacent matrix of the sanitized graph is reconstructed. In addition,a set of experiments is conducted to evaluate its feasibility,availability and strengths using three analysis techniques: degree distribution,shortest path,and clustering coefficients.
There are growing concerns surrounding the data security of social networks because large amount of user information and sensitive data are collected. Differential privacy is an effective meth- od for privacy protection that can provide rigorous and quantitative protection. Concerning the appli- cation of differential privacy in social networks, this paper analyzes current trends of research and provides some background information including privacy protection standards and noise mechanisms. Focusing on the privacy protection of social network data publishing, a graph-publishing model is designed to provide differential privacy in social networks via three steps: Firstly, according to the features of social network where two nodes that possess certain common properties are associated with a higher probability, a raw graph is divided into several disconnected sub-graphs, and correspond- ingly dense adjacent matrixes and the number of bridges are obtained. Secondly, taking the advan- tage of quad-trees, dense region exploration of the adjacent matrixes is conducted. Finally, using an exponential mechanism and leaf nodes of quad-trees, an adjacent matrix of the sanitized graph is re- constructed. In addition, a set of experiments is conducted to evaluate its feasibility, availability and strengths using three analysis techniques: degree distribution, shortest path, and clustering coeffi- cients.
作者
王俊丽
Yang Li
Wu Yuxi
Guan Min
Wang Junli;Yang Li;Wu Yuxi;Guan Min(Department of Computer Science and Technology, Tongji University, Shanghai 201804, P. R. China)
基金
Supported by the National Natural Science Foundation of China(No.61105047)
the National High Technology Research and Development Program of China(No.2015IM030300)
the Science and Technology Committee of Shanghai Support Project(No.14JC1405800)
the Project of the Central Universities Fundamental Research of Tongji University