Title :
Research on Diversity of Sensitive Attribute of K-Anonymity
Author :
Ren, Xiangmin ; Yang, Jing ; Wei, Fengmei
Author_Institution :
Coll. of Comput. Sci. & Technol., Harbin Eng. Univ., Harbin, China
Abstract :
The common way to protect privacy is to use K-anonymity in data publishing. This paper will analyse comprehensively the current research situation of K-anonymity model used to prevent privacy leaked in data publishing, we study the characteristics of sensitive attribute diversity of K-Anonymity, and propose CBK(L,K)-Anonymity algorithm in order to solve the problem of privacy information leakage in publishing the data, it can make anonymous data effectively resist background knowledge attack and homogeneity attack , and can solve diversity of sensitive attribute. In addition, we will extend our ideas for handling how to solve privacy information leakage problem by using CBK(L,K)-Anonymity algorithm in another paper.
Keywords :
data privacy; publishing; CBK-anonymity algorithm; data publishing; k-anonymity attribute; privacy information leakage problem; privacy protection; sensitive attribute diversity; Algorithm design and analysis; Cancer; Clustering algorithms; Data privacy; Lungs; Privacy; Publishing;
Conference_Titel :
Database Technology and Applications (DBTA), 2010 2nd International Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6975-8
Electronic_ISBN :
978-1-4244-6977-2
DOI :
10.1109/DBTA.2010.5659106