Research on the Personalized Privacy Preserving Distributed Data Mining

被引：3

作者：

Shen, Yanguang ^{[1
]}

Shao, Hui ^{[1
]}

Li, Yan ^{[1
]}

机构：

[1] Hebei Univ Engn, Sch Informat Sci & Elect Engn, Handan, Peoples R China

来源：

2009 SECOND INTERNATIONAL CONFERENCE ON FUTURE INFORMATION TECHNOLOGY AND MANAGEMENT ENGINEERING, FITME 2009 | 2009年

关键词：

personalized privacy preserving; distributed data mining; decision tree classification; SMC; K-anonymity;

D O I：

10.1109/FITME.2009.115

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In this paper we studied privacy preserving distributed data mining.The existing methods focus on a universal approach that exerts preservation in the same degree for all persons, without catering for their concrete needs. In view of this we innovatively proposed a new framework combining the Secure Multiparty Computation(SMC) with K-anonymity technology, and achieved personalized privacy preserving distributed data mining based on decision tree classification algorithm. Compared with other algorithms our methord could make a good trade-off point between privacy and accuracy, with high efficiency and low-overhead of computing and communication.

引用

页码：436 / 439

页数：4

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