Other Knowledge Hiding Methodologies

Abstract

Association rule hiding algorithms aim at protecting sensitive knowledge captured in the form of frequent itemsets or association rules. However, (sensitive) knowledge may appear in various forms directly related to the applied data mining algorithm that achieved to expose it. Consequently, a set of hiding approaches have been proposed over the years to allow for the safeguarding of sensitive knowledge exposed by data mining tasks such as clustering, classification and sequence mining. In this chapter, we briefly discuss some state-of-the-art approaches for the hiding of sensitive knowledge that is depicted in any of the aforementioned formats.