An Association Rule hiding Algorithm for Privacy Preserving Data Mining

Abstract

Privacy preserving data mining is a research area concerned with the privacy driven from personally identifiable information when considered for data mining. This paper addresses the privacy problem by considering the privacy and algorithmic requirements simultaneously. The objective of this paper is to implement an association rule hiding algorithm for privacy preserving data mining which would be efficient in providing confidentiality and improve the performance at the time when the database stores and retrieves huge amount of data. This paper compares the performance of proposed algorithm with the two existing algorithms namely ISL and DSR.