A Comprehensive Study of Privacy Preservation Techniques in a Distributed Association Rule Mining

Abstract

rule mining is a popular technique in data mining process which tries to find interesting associations and correlations among various data items in a transaction. Many business share data with others, outsource their business data for specific business solution. In these situations, the sensitive information leakage is the biggest problem. Strong and efficient privacy preserving techniques are needed to secure organizations data during third party sharing. In this paper, a comprehensive study of various methods for privacy preservation is presented which evaluates and analyzes various techniques for maintaining privacy during association rule mining process. Moreover, paper also prospects the development of privacy preservation for future applications.