A Differential Privacy Topology Scheme For Average Path Length Query

Privacy protection of sensitive information has become an urgent problem to be solved in social networks. Differential privacy is used in many privacy protection methods because it can provide strong protection. Most of existing differential privacy scheme mainly implements the privacy protection on nodes or edges in the network by perturbing the data query results. The privacy protection requirements of multiple types of information cannot be satisfied in these schemes. In order to solve these issues, a differential privacy security mechanism with average path length (APL) query is proposed in this paper, which realize the privacy protection of both edge weights and network vertices. The reasons for choosing this attribute as the query function are analyzed. The global sensitivity of APL query under the need of node privacy protection and edge-weighted privacy protection is proved. Based on previous studies, the concept of edge-weighted neighborhood graph in differential privacy is proposed. The relationship between data availability and privacy control parameters in differential privacy is analyzed through experiments.