DP-UserPro:differentially private user profile construction and publication  

作　　者：Zheng HUO Ping HE Lisha HU Huanyu ZHAO 

机构地区：[1]Information Technology School,Hebei University of Economics and Business,Shijiazhuang 050061,China [2]The Institute of Applied Mathematics,Hebei Academy of Sciences,Shijiazhuang 050051,China [3]Hebei Authentication Technology Engineering Research Center,Shijiazhuang 050051,China

出　　处：《Frontiers of Computer Science》2021年第5期197-206,共10页中国计算机科学前沿（英文版）

基　　金：the National Natural Science Foundation of China(Grant No.62002098);Natural Science Foundation of Hebei Province(F2020207001,F2019207061);the Scientific Research Projects of Hebei Education Department(QN2018116);the Research Foundation of Hebei University of Economics and Business(2018QZ04,2019JYQ08).

摘　　要：User profiles are widely used in the age of big data.However,generating and releasing user profiles may cause serious privacy leakage,since a large number of personal data are collected and analyzed.In this paper,we propose a differentially private user profile construction method DP-UserPro,which is composed of DP-CLIQUE and privately top-κtags selection.DP-CLIQUE is a differentially private high dimensional data cluster algorithm based on CLIQUE.The multidimensional tag space is divided into cells,Laplace noises are added into the count value of each cell.Based on the breadth-first-search,the largest connected dense cells are clustered into a cluster.Then a privately top-κtags selection approach is proposed based on the score function of each tag,to select the most importantκtags which can represent the characteristics of the cluster.Privacy and utility of DP-UserPro are theoretically analyzed and experimentally evaluated in the last.Comparison experiments are carried out with Tag Suppression algorithm on two real datasets,to measure the False Negative Rate(FNR)and precision.The results show that DP-UserPro outperforms Tag Suppression by 62.5%in the best case and 14.25%in the worst case on FNR,and DP-UserPro is about 21.1%better on precision than that of Tag Suppression,in average.

关 键 词：user profile DP-CLIQUE CLUSTERING differential privacy recommender system 

分 类 号：TP309[自动化与计算机技术—计算机系统结构]