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Using sample size to limit exposure to data mining

Article type: Research Article

Authors: Clifton, Chris

Affiliations: The MITRE Corporation, 202 Burlington Road, Bedford, MA 01730-1420, USA. Tel.: +1 781 271 2390; Fax: +1 781 271 2352; E-mail: clifton@mitre.org

Abstract: Data mining introduces new problems in database security. The basic problem of using non-sensitive data to infer sensitive data is made more difficult by the “probabilistic” inferences possible with data mining. This paper shows how lower bounds from pattern recognition theory can be used to determine sample sizes where data mining tools cannot obtain reliable results.

DOI: 10.3233/JCS-2000-8403

Journal: Journal of Computer Security, vol. 8, no. 4, pp. 281-307, 2000

Published: 1 October 2000
Price: EUR 27.50
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