Volume 4 Number 6 (Aug. 2009)
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JSW 2009 Vol.4(6): 555-562 ISSN: 1796-217X
doi: 10.4304//jsw.4.6.555-562

A Novel Method for Privacy Preserving in Association Rule Mining Based on Genetic Algorithms

Mohammad Naderi Dehkordi1, Kambiz Badie2, Ahmad Khadem Zadeh2
1Ph.D Student, Science & Research Branch, Islamic Azad University (IAU) Department of Computer Engineering, Tehran, Iran
2Iran Telecom Research Center, Tehran, Iran

Abstract—Extracting of knowledge form large amount of data is an important issue in data mining systems. One of most important activities in data mining is association rule mining and the new head for data mining research area is privacy of mining. Today association rule mining has been a hot research topic in Data Mining and security area. A lot of research has done in this area but most of them focused on perturbation of original database heuristically. Therefore the final accuracy of released database falls down intensely. In addition to accuracy of database the main aspect of security in this area is privacy of database that is not warranted in most heuristic approaches, perfectly. In this paper we introduce new multi-objective method for hiding sensitive association rules based on the concept of genetic algorithms. The main purpose of this method is fully supporting security of database and keeping the utility and certainty of mined rules at highest level.

Index Terms—Data Mining, Privacy Preserving, Sensitive Association Rules, Genetic Algorithms


Cite: Mohammad Naderi Dehkordi, Kambiz Badie, Ahmad Khadem Zadeh, "A Novel Method for Privacy Preserving in Association Rule Mining Based on Genetic Algorithms," Journal of Software vol. 4, no. 6, pp. 555-562, 2009.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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