A unified framework for protecting sensitive association rules in business collaboration
Stanley Robson de Medeiros Oliveira, Osmar R. Zai͏̈ane · International Journal of Business Intelligence and Data Mining · 2006
The sharing of association rules has been proven beneficial in business collaboration, but requires privacy safeguards. One may decide to disclose only part of the knowledge and conceal strategic patterns called sensitive rules. The challenge here is how to protect the sensitive rules without losing the benefit of mining. To address this problem, we propose a unified framework that combines: a set of algorithms to protect sensitive knowledge; retrieval facilities to speed up the process of knowledge protecting; and a set of metrics to evaluate the effectiveness of the proposed algorithms in terms of information loss and private information disclosure.