On the Comparison of Innovative Perturbative Masking Technique and Existing Perturbative Masking Techniques

Abstract— The increasing facility to track and collect large amounts of data with the use of this has led to an interest in the development of data mining algorithms which preserve user privacy. With the growth of data analysis and processing technique, the privacy disclosure problem about individual or company is inevitably exposed when releasing or sharing data to mine useful decision information and knowledge, then give the birth to the research field on privacy preserving data mining. A number of methods have recently been proposed for privacy preserving data mining. In this paper we discuss implement new masking techniques Data Transitive Technique to compare the existing Perturbative masking techniques in privacy preserving data mining.