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.
Note
Thirteenth Annual IFIP WG 11.3 Working Conference on Database Security
July 26-28, 1999 in Seattle, WA
Expanded version invited for submission to Journal of Computer Security, IOS Press
