A Survey on Association Rule Hiding in Privacy Preserving Data Mining

Data mining has been used as a public utility in extracting knowledge from databases during recent years. Developments in data mining and availability of data and private information are the biggest challenge in this regard. Preservation of privacy in data mining has emerged as an absolute prerequisite for exchanging confidential information in terms of data analysis, validation, and publishing. The main purpose of techniques and algorithms in privacy preserving data mining is non-disclosure of sensitive and private data with minimum changes in databases so that it would not have adverse effects on the rest of data. The present paper intends to present a brief review of methods and techniques regarding privacy of data mining in association rules, their classification and finally, classification of hiding algorithms of association rules followed by a comparison between a numbers of these algorithms.