Li, Jiuyong and Wang, Hua and Jin, Huidong and Yong, Jianming (2006) Current developments of k-anonymous data releasing. In: National e-Health Privacy and Security Symposium 2006, 24-26 October 2006, Brisbane.
![[img]](http://eprints.usq.edu.au/style/images/fileicons/application_pdf.png)
|
PDF
13.pdf Download (97Kb) |
Abstract
Disclosure-control is a traditional statistical methodology for protecting privacy when data is released for analysis. Disclosure-control methods have enjoyed
a revival in the data mining community, especially after the introduction of the k-anonymity model by Samarati and Sweeney. Algorithmic advances on k-anonymisation provide simple and effective approaches to protect private information of individuals via only releasing k-anonymous views of a data set.
Thus, the k-anonymity model has gained increasing popularity. Recent research identifies some drawbacks of the k-anonymity model and presents enhanced k-
anonymity models. This paper reviews problems of the k-anonymity model and its enhanced variants, and different methods for implementing k-anonymity. It compares the k-anonymity model with the secure multiparty computation-based privacy-preserving techniques in the data mining literature. The paper also discusses further development directions of the k-anonymous data releasing.
|
Statistics for this ePrint Item |
| Item Type: | Conference or Workshop Item (Commonwealth Reporting Category E) (Paper) |
|---|---|
| Refereed: | Yes |
| Item Status: | Live Archive |
| Faculty / Department / School: | Historic - Faculty of Sciences - Department of Maths and Computing |
| Date Deposited: | 11 Oct 2007 00:39 |
| Last Modified: | 25 Nov 2013 01:49 |
| Uncontrolled Keywords: | k-Anonymous, data privacy |
| Fields of Research : | 08 Information and Computing Sciences > 0806 Information Systems > 080604 Database Management |
| URI: | http://eprints.usq.edu.au/id/eprint/1307 |
Actions (login required)
 |
Archive Repository Staff Only |