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Data mining introduces new problems in database security. The basicproblem of using non-sensitive data to infer sensitive data is mademore difficult by the "probabilistic" inferences possible with datamining. This paper shows how lower bounds from pattern recognitiontheory can be used to determine sample sizes where data miningtools cannot obtain reliable results.