A Survey on Association Rule Hiding in Privacy Preserving Data Mining

  • Arezoo Hekmatyar Islamic Azad University, Najafabad, Iran
  • Naser Nematbakhsh Islamic Azad University, Najafabad, Iran
  • Mohammad Naderi Dehkordi Islamic Azad University, Najafabad, Iran
Keywords: Privacy Preserving Data Mining, Association Rule, Sensitive Data, Data Disclosure

Abstract

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. Privacy preserving data mining is a response to this big challenge. 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.

Author Biographies

Arezoo Hekmatyar, Islamic Azad University, Najafabad, Iran
Department of Computer Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
Naser Nematbakhsh, Islamic Azad University, Najafabad, Iran
Department of Computer Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
Mohammad Naderi Dehkordi, Islamic Azad University, Najafabad, Iran
Department of Computer Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran

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Published
2016-12-03
How to Cite
Hekmatyar, A., Nematbakhsh, N., & Naderi Dehkordi, M. (2016). A Survey on Association Rule Hiding in Privacy Preserving Data Mining. Majlesi Journal of Electrical Engineering, 10(4). Retrieved from http://mjee.iaumajlesi.ac.ir/index/index.php/ee/article/view/2082
Section
Articles