Publishing Weighted Graph with Node Differential Privacy

Abstract

At present, how to protect user privacy and security while publishing user data has become an increasingly important problem. Differential privacy is mainly divided into two directions in graph data publishing. One is to publish the statistical characteristics of the graph that meets the differential privacy, and the other is to publish the synthesis graph that meets the differential privacy. This paper proposes a weighted graph publishing method based on node difference privacy. First, this paper proposes a projection method that constrains the degree of nodes and the number of triangles and reduces the increase in noise by reducing the sensitivity. Afterward, select appropriate statistical characteristics of the weighted graph to form node attributes as the parameters of the syn-thesis weighted graph. The next part proposes a graph publishing method based on node attributes and weights. This method synthesizes the initial graph according to the degree in the node attribute. It then adds or deletes the edges of the initial graph according to the number of triangles in the node attribute to obtain the final synthesis graph. Finally, this paper verifies the weighted graph publishing method proposed on three data sets. The results show that the method proposed in this paper satisfies the different privacy conditions of nodes while maintaining certain utility.