A Framework for Enforcing Privacy in Mining Frequent Patterns
Stanley Robson de Medeiros Oliveira, Osmar R. Zai͏̈ane · 2002
this paper, we propose a new framework for enforcing privacy in mining frequent itemsets. We combine, in a single framework, techniques for eciently hiding restrictive patterns: a transaction retrieval engine relying on an inverted le and Boolean queries; and a set of algorithms to \\sanitize" a database. In addition, weintroduce mining performance measures for frequent itemsets that quantify the fraction of mining patterns which are preserved after sanitizing a database. We also report the results of a performance evaluation of our research prototype and an analysis of the results