Microdata protection through approximate microaggregation

Sun, Xiaoxun and Wang, Hua and Li, Jiuyong (2009) Microdata protection through approximate microaggregation. In: ACSC 2009: 32nd Australasian Computer Science Conference, 19-23 Jan 2009, Wellington, New Zealand.

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Microdata protection is a hot topic in the field of Statistical Disclosure Control, which has gained special interest after the disclosure of 658000 queries by the America Online (AOL) search engine in August 2006. Many algorithms, methods and properties have been proposed to deal with microdata disclosure. One of the emerging
concepts in microdata protection is k-anonymity, introduced by Samarati and Sweeney. k-anonymity provides a simple and efficient approach to protect private individual information and is gaining increasing popularity. k-anonymity requires that every record in the microdata table released be indistinguishably related to no fewer than k respondents.

In this paper, we apply the concept of entropy to propose a distance metric to evaluate the amount of mutual information among records in microdata, and propose a method of constructing dependency tree to find the key attributes, which we then use to process approximate microaggregation. Further, we adopt this new microaggregation technique to study $k$-anonymity problem, and an efficient algorithm is developed. Experimental results show that the proposed microaggregation technique is efficient and effective in the terms of running time and information loss.

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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. Copyright 2009, Australian Computer Society, Inc. This paper appeared at the Thirty-Second Australasian Computer Science Conference (ACSC2009), Wellington, New Zealand. Conferences in Research and Practice in Information Technology (CRPIT), Vol. 91. Bernard Mans, Ed. Reproduction for academic, not-for profit purposes permitted provided this text is included.
Faculty/School / Institute/Centre: Historic - Faculty of Sciences - Department of Maths and Computing (Up to 30 Jun 2013)
Faculty/School / Institute/Centre: Historic - Faculty of Sciences - Department of Maths and Computing (Up to 30 Jun 2013)
Date Deposited: 08 Jul 2010 12:36
Last Modified: 19 Sep 2012 00:04
Uncontrolled Keywords: microdata protection; privacy
Fields of Research (2008): 08 Information and Computing Sciences > 0803 Computer Software > 080303 Computer System Security
08 Information and Computing Sciences > 0806 Information Systems > 080609 Information Systems Management
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4604 Cybersecurity and privacy > 460499 Cybersecurity and privacy not elsewhere classified
46 INFORMATION AND COMPUTING SCIENCES > 4609 Information systems > 460908 Information systems organisation and management
Socio-Economic Objectives (2008): B Economic Development > 89 Information and Communication Services > 8999 Other Information and Communication Services > 899999 Information and Communication Services not elsewhere classified
URI: http://eprints.usq.edu.au/id/eprint/4732

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