Volume 7 Number 7 (Jul. 2012)
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JSW 2012 Vol.7(7): 1649-1656 ISSN: 1796-217X
doi: 10.4304/jsw.7.7.1649-1656

Research on Privacy Preserving on K-anonymity

Yun Pan1, Xiao-ling Zhu2, and Ting-gui Chen3
1School of Computer Science & Information Engineering, Zhejiang Gongshang University, Hangzhou, China
2College of Computer Science & Information Engineering, Zhejiang Gongshang University, Hangzhou, China
3Contemporary Business and Trade Research Center, Zhejiang Gongshang University, Hangzhou, China

Abstract—The disclosure of sensitive information has become prominent nowadays; privacy preservation has become a research hotspot in the field of data security. Among all the algorithms of privacy preservation in data mining, K-anonymity is a kind of common and valid algorithm in privacy preservation, which can effectively prevent the loss of sensitive information under linking attacks, and it is widely used in various fields recent years. This article based on the existing K-anonymity privacy preservation of the basic ideas and concepts, K-anonymity model, and enhanced the K-anonymity model, and gives a simple example to compare each algorithm; finally, it prospected the development direction of K-anonymity on privacy preservation.

Index Terms—data mining; privacy preservation; Kanonymity; generalization & suppression; the enhanced Kanonymity


Cite: Yun Pan, Xiao-ling Zhu, and Ting-gui Chen, "Research on Privacy Preserving on K-anonymity," Journal of Software vol. 7, no. 7, pp. 1649-1656, 2012.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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