New Algorithm for Sensitive Rule Hiding Using Data Distortion Technique

Abstract

Data mining is the process of extracting hidden patterns of data. Association rule mining is an important data mining task that finds interesting association among a large set of data item. It may disclose pattern and various kinds of sensitive information. Such information may be protected against unauthorized access. Association rule hiding is one of the techniques of privacy preserving data mining to protect the association rules generated by association rule mining. This paper adopts data distortion technique for hiding sensitive association rules. Algorithms based on this technique either hide a specific rule using data alteration technique or hide the rules depending on the sensitivity of the items to be hidden. In the proposed technique, positions of sensitive items are altered while maintaining the support. The proposed technique uses the idea of representative rules to prune the rules first and then hides the sensitive rules.