(p+, α)-sensitive k-anonymity: a new enhanced privacy protection model

Sun, Xiaoxun and Wang, Hua and Truta, Traian Marius and Li, Jiuyong and Li, Ping (2008) (p+, α)-sensitive k-anonymity: a new enhanced privacy protection model. In: 8th IEEE International Conference on Computer and Information Technology, 8-11 Jul 2008, Sydney, Australia.

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Abstract

Publishing data for analysis from a microdata table containing sensitive attributes, while maintaining individual privacy, is a problem of increasing significance today. The k-anonymity model was proposed for privacy preserving data publication. While focusing on identity disclosure, k-anonymity model fails to protect attribute disclosure to some extent. Many efforts are made to enhance the kanonymity model recently. In this paper, we propose a new privacy protection model called (p+, α)-sensitive kanonymity, where sensitive attributes are first partitioned into categories by their sensitivity, and then the categories that sensitive attributes belong to are published. Different from previous enhanced k-anonymity models, this model allows us to release a lot more information without compromising privacy. We also provide testing and heuristic generating algorithms. Experimental results show that our introduced model could significantly reduce the privacy breach.

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Item Type:	Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed:	Yes
Item Status:	Live Archive
Additional Information:	Deposited in accordance with the copyright policy of the publisher. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. Copyright 2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Faculty / Department / School:	Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited:	14 Jul 2008 00:04
Last Modified:	02 Jul 2013 23:04
Uncontrolled Keywords:	k-anonymity models; privacy protection models; (p+, α)-sensitive k-anonymity model
Fields of Research :	08 Information and Computing Sciences > 0806 Information Systems > 080604 Database Management 08 Information and Computing Sciences > 0803 Computer Software > 080303 Computer System Security 08 Information and Computing Sciences > 0804 Data Format > 080499 Data Format not elsewhere classified
Socio-Economic Objective:	E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI:	doi: 10.1109/CIT.2008.4594650
URI:	http://eprints.usq.edu.au/id/eprint/4263

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