Extended K-anonymity models against attribute disclosure

Sun, Xiaoxun and Wang, Hua and Sun, Lili (2009) Extended K-anonymity models against attribute disclosure. In: NSS 2009: 3rd International Conference on Network and System Security, 19-21 Oct 2009, Gold Coast, Australia.

Abstract

P-sensitive K-anonymity model has been recently defined as a sophistication of K-anonymity. This new property requires that there be at least P distinct values for each sensitive attribute within the records sharing a combination of key attributes. However, as shown in this paper, it may not protect sensitive information in some way. In this paper, we empirically investigate two enhanced K-anonymity models. Instead of publishing original specific sensitive attributes, the new models publish the categories that the sensitive values belong to. We propose a top-down approach to implement two enhanced models and show in the comprehensive experimental evaluations that the two new introduced models are practical in terms of effectiveness and efficiency.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Depositing User: Mr Xiaoxun Sun
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 10 Aug 2010 12:15
Last Modified: 02 Jul 2013 23:32
Uncontrolled Keywords: attribute disclosure; extended k-anonymity models; p-sensitive k-anonymity model; sensitive information; specific sensitive attributes; top-down approach
Fields of Research (FOR2008): 08 Information and Computing Sciences > 0806 Information Systems > 080604 Database Management
08 Information and Computing Sciences > 0802 Computation Theory and Mathematics > 080201 Analysis of Algorithms and Complexity
08 Information and Computing Sciences > 0803 Computer Software > 080303 Computer System Security
Socio-Economic Objective (SEO2008): E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI: doi: 10.1109/NSS.2009.23
URI: http://eprints.usq.edu.au/id/eprint/6321

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