同济大学学报（自然科学版）2017，Vol.45Issue(8)：1227-1232,6.DOI:10.11908/j.issn.0253-374x.2017.08.018
基于差分隐私保护的社交网络发布图生成模型
Differential Privacy Protection Based Generation Model of Social Network Publication Graph
摘要
Abstract
When Social Network helps people build various social networking applications,a large number of user information and sensitive data will be collected in the mean time,and through the analysis of these data,some potential privacy information may be disclosed.At present,differential privacy protection model provides a rigorous and quantitative representation of the risk of privacy disclosure,which greatly guarantees the availability of data.In this paper,a generation model of social network publication graph is designed to meet the differential privacy protection.First the social network structure is represented as a graph model,and the original graph is classified into multiple sub-graphs according to the characteristics of nodes.Then intensive regional of every subgraph is divided with a Quadtree method,noises of differential privacy protection are added into leaf nodes of the trees,and publication graph is generated by the way of sub-graph reconstruction,.Finally,the feasibility and usefulness of the model is verified by the statistical analysis,such as the degree distribution,the shortest path and the clustering coefficient.关键词
差分隐私保护/社交网络/发布图生成模型Key words
differential privacy protection/social network/graph-publishing generation model分类
信息技术与安全科学引用本文复制引用
王俊丽,柳先辉,管敏..基于差分隐私保护的社交网络发布图生成模型[J].同济大学学报（自然科学版）,2017,45(8):1227-1232,6.基金项目
国家“八六三”高技术研究发展计划(2015IM030300) （2015IM030300）
上海市科技创新计划(15DZ1101202) （15DZ1101202）
上海市科委项目(14JC1405800) （14JC1405800）
同济大学中央高校基本科研业务费 （）
