DocumentCode :
2675619
Title :
A Multi-Dimensional K-Anonymity Model for Hierarchical Data
Author :
Ye, Xiaojun ; Jin, Lei ; Li, Bin
Author_Institution :
Key Lab. for Inf. Syst. Security Sch. of Software, Tsinghua Univ., Beijing
fYear :
2008
fDate :
3-5 Aug. 2008
Firstpage :
327
Lastpage :
332
Abstract :
For improving the usability of the anonymous result, it is important to comply with the hierarchical structure when generalizing quasi-identifying attributes with hierarchical characteristics. We propose an unrestricted multi-dimensional anonymization model which combines global recoding and local recoding methods. The bottom-up anonymization algorithm with the minimal coverage subgraph constraint and the anonymization metric are proposed. The experiment results justify the effectiveness and scalability of this model.
Keywords :
data privacy; graph theory; data privacy; global recoding methods; hierarchical data; hierarchical structure; local recoding methods; minimal coverage subgraph constraint; multidimensional K-anonymity model; unrestricted multidimensional anonymization model; Cancer; Data security; Diseases; Electronic commerce; Information security; Information systems; Laboratories; Multidimensional systems; Scalability; Usability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronic Commerce and Security, 2008 International Symposium on
Conference_Location :
Guangzhou City
Print_ISBN :
978-0-7695-3258-5
Type :
conf
DOI :
10.1109/ISECS.2008.113
Filename :
4606081
Link To Document :
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