典型文献
Enhanced Privacy Preserving for Social Networks Relational Data Based on Personalized Differential Privacy
文献摘要：
With the popularization and develop-ment of social software,more and more people join the social network,which produces a lot of valuable informa-tion,but also contains plenty of sensitive privacy informa-tion.To achieve the personalized privacy protection of masssive social network relational data,a privacy enhance-ment method for social networks relational data based on personalized differential privacy is proposed.And a di-mensionality reduction segmentation sampling(DRS-S)algorithm is proposed to implement this method.First,in order to solve the problem of inefficiency caused by the excessive amount of data in social networks,dimension re-duction and segmentation are carried out to divide the data into groups.According to the privacy protection re-quirements of different users,we adopt sampling method to protect users with different privacy requirements at different levels,so as to realize personalized different pri-vacy.After that,the noise is added to the protected data to satisfy the privacy budget.Then publish the social net-work data.Finally,the proposed algorithm is compared with the traditional personalized differential privacy(PDP)algorithm and privacy preserving approach based on clustering and noise(PBCN)in real data set,the ex-perimental results demonstrate that the quality of pri-vacy protection and data availability of DRS-S are better than that of PDP algorithm and PBCN algorithm.
文献关键词：
中图分类号：
作者姓名：
KANG Haiyan;JI Yuanrui;ZHANG Shuxuan
作者机构：
School of Information Management,Beijing Information Science and Technology University,Beijing 100192,China;Computer School,Beijing Information Science and Technology University,Beijing 100192,China
文献出处：
引用格式：
[1]KANG Haiyan;JI Yuanrui;ZHANG Shuxuan-.Enhanced Privacy Preserving for Social Networks Relational Data Based on Personalized Differential Privacy)[J].电子学报（英文）,2022(04):741-751
A类：
masssive,mensionality,PBCN
B类：
Enhanced,Privacy,Preserving,Social,Networks,Relational,Data,Based,Personalized,Differential,With,popularization,develop,social,software,more,people,join,which,produces,lot,valuable,informa,but,also,contains,plenty,sensitive,privacy,To,achieve,personalized,protection,relational,data,enhance,method,networks,differential,proposed,And,reduction,segmentation,sampling,DRS,algorithm,implement,this,First,order,solve,problem,inefficiency,caused,by,excessive,amount,dimension,carried,out,divide,into,groups,According,users,we,adopt,requirements,levels,realize,After,that,noise,added,protected,satisfy,budget,Then,publish,Finally,compared,traditional,PDP,preserving,approach,clustering,set,perimental,results,demonstrate,quality,availability,better,than
AB值：
0.466011
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