A family of enhanced (L,alpha)- diversity models for privacy preserving data publishing

Sun, Xiaoxun and Li, Min and Wang, Hua (2011) A family of enhanced (L,alpha)- diversity models for privacy preserving data publishing. Future Generation Computer Systems: The International Journal of Grid Computing: Theory, Methods and Applications, 27 (3). pp. 348-356. ISSN 0167-739X

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Abstract

Privacy preservation is an important issue in the release of data for mining purposes. Recently, a novel l-diversity privacy model was proposed, however, even an l-diverse data set may have some severe problems leading to reveal individual sensitive information. In this paper, we remedy the problem by introducing distinct (l, )-diversity, which, intuitively, demands that the total weight of the sensitive values in a given QI-group is at least , where the weight is controlled by a pre-defined recursive metric system. We provide a thorough analysis of the distinct (l, )-diversity and prove that the optimal distinct (l, )-diversity problem with its two variants entropy (l, )-diversity and recursive (c, l, )-diversity are NP-hard, and propose a top-down anonymization approach to solve the distinct (l,)-diversity problem with its variants. We show in the extensive experimental evaluations that the proposed methods are practical in terms of utility measurements and can be implemented efficiently.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Author version deposited in accordance with the copyright policy of the publisher.
Depositing User: Dr Hua Wang
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 19 Jan 2011 12:17
Last Modified: 19 Aug 2014 05:41
Uncontrolled Keywords: anonymization; data publishing; data sets; experimental evaluation; NP-hard; privacy models; privacy preservation; sensitive informations; topdown
Fields of Research (FOR2008): 08 Information and Computing Sciences > 0804 Data Format > 080402 Data Encryption
08 Information and Computing Sciences > 0803 Computer Software > 080303 Computer System Security
08 Information and Computing Sciences > 0806 Information Systems > 080608 Information Systems Development Methodologies
Socio-Economic Objective (SEO2008): B Economic Development > 89 Information and Communication Services > 8902 Computer Software and Services > 890299 Computer Software and Services not elsewhere classified
Identification Number or DOI: doi: 10.1016/j.future.2010.07.007
URI: http://eprints.usq.edu.au/id/eprint/8462

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