Authors: Mohammad Naderi Dehkordi, Kambiz Badie, Ahmad Khadem Zadeh
Addresses: Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran. ' IT Research Faculty, Iran Telecom Research Center, End of North Kargar Avenue, Tehran, Iran. ' Education and National Scientific and International Scientific Cooperation Department, Iran Telecom Research Center, End of North Kargar Avenue, Tehran, Iran
Abstract: Privacy preserving association rule mining has been an active research area since recently. So data mining techniques have been developed in many applications. On the other hand, it also causes an intimidation to privacy of sensitive information. We investigate to find an appropriate balance between an urgency of need for privacy and information extraction on association rules. In this paper, we propose a novel technique for concealing sensitive association rules. In our approach, we do some perturbation in original dataset based on genetic algorithms with suitable fitness function to hide sensitive rules and minimum number of modifications. Finally, a set of experiments is performed to show the effectiveness of our approach.
Keywords: association rule mining; association rule hiding; sensitive association rules; genetic algorithms; GAs; privacy preservation; data mining.
International Journal of Rapid Manufacturing, 2009 Vol.1 No.2, pp.128 - 149
Published online: 28 Nov 2009 *Full-text access for editors Access for subscribers Purchase this article Comment on this article