Study on distributed privacy preserving data mining

被引:0
|
作者
Wang, Binli [1 ]
Shen, Yanguang [1 ]
机构
[1] Hebei Univ Engn, Handan 056038, Hebei, Peoples R China
关键词
Data mining; Privacy preserving; Distributed environment; perturbation; SMC; Anonymization;
D O I
10.1260/1708-5284.11.2.163
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Recently, with the rapid development of network, communications and computer technology, privacy preserving data mining (PPDM) has become an increasingly important research in the field of data mining. In distributed environment, how to protect data privacy while doing data mining jobs from a large number of distributed data is more far-researching. This paper describes current research of PPDM at home and abroad. Then it puts emphasis on classifying the typical uses and algorithms of PPDM in distributed environment, and summarizing their advantages and disadvantages. Furthermore, it points out the future research directions in the field.
引用
收藏
页码:163 / 169
页数:7
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