Systematic clustering-based microaggregation for statistical disclosure control

Kabir, Md Enamul and Wang, Hua (2010) Systematic clustering-based microaggregation for statistical disclosure control. In: NSS 2010: International Conference on Network and System Security , 1-3 Sep 2010, Melbourne, Australia.

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Abstract

Microdata protection in statistical databases has recently become a major societal concern. Microaggregation for Statistical Disclosure Control (SDC) is a family of methods to protect microdata from individual identification. Microaggregation works by partitioning the microdata into groups of at least k records and then replacing the records in each group with the centroid of the group. This paper presents a clusteringbased microaggregation method to minimize the information loss. The proposed technique adopts to group similar records together in a systematic way and then anonymized with the centroid of each group individually. The structure of systematic clustering problem is defined and investigated and an algorithm of the proposed problem is developed. Experimental results show that our method attains a reasonable dominance with respect to both information loss and execution time than the most popular heuristic algorithm called Maximum Distance to Average Vector (MDAV).


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Accepted version deposited in accordance with the copyright policy of the publisher.
Depositing User: Mr Md Enamul Kabir
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 11 Jul 2011 01:50
Last Modified: 03 Jul 2013 00:27
Uncontrolled Keywords: privacy; microaggregation; microdata protection; k-anonymity; disclosure control
Fields of Research (FOR2008): 01 Mathematical Sciences > 0104 Statistics > 010499 Statistics not elsewhere classified
08 Information and Computing Sciences > 0804 Data Format > 080402 Data Encryption
08 Information and Computing Sciences > 0803 Computer Software > 080303 Computer System Security
Socio-Economic Objective (SEO2008): E Expanding Knowledge > 97 Expanding Knowledge > 970101 Expanding Knowledge in the Mathematical Sciences
Identification Number or DOI: doi: 10.1109/NSS.2010.66
URI: http://eprints.usq.edu.au/id/eprint/18231

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