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

[PDF]

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.