Hiding Sensitive Itemsets Using Sibling Itemset Constraints

Data collection and processing progress made data mining a popular tool among organizations in the last decades. Sharing information between companies could make this more beneficial for each party. However, there is risk of sensitive knowledge disclosure. Shared should be modified such way that relationships would hidden. Since discovery frequent itemsets one most effective tools firms use, privacy-preserving techniques are necessary continuing itemset mining. There two types approaches algorithmic nature: heuristic exact. This paper presents an exact hiding approach, which uses constraints better solution terms side effects minimum distortion on database. creates asymmetric relation original sanitized To lessen hiding, we introduced sibling concept used generating constraints. Additionally, our approach does not require executed before process. gives advantage total running time. We give evaluation algorithm some benchmark datasets. Our results show effectiveness elimination prior time efficient.