A Novel Approach of Association Rule Hiding Using DBCT (Distortion, Blocking and Cryptographic Technique)

Abstract

Associative rule hiding is a technique used in hiding sensitive data, during data processing to secure the sensitive association rules generated using association rule mining. Several methods were planned within the literature for hiding sensitive data items. Few apply distributed databases across various sites, few indulged data perturbation, and few utilized clustering and few of them employ data distortion technique. Algorithms supporting this method will follow either of the following two techniques. Hide a particular rule with the help of data alteration technique or hide the principles relying on the sensitivity of the items to be hidden. The proposed perspective dependent on data distortion technique which modifies the position of the sensitive items, yet its support is not at all altered and also used the ideology of representative results to shear the rules initially and then hides those sensitive rules. Experimental results exhibit that proposed method hides lot of rules at a minimum range of database scans in contrast to existing algorithms supporting data distortion technique.