A novel method for privacy preserving in association rule mining based on genetic algorithms

被引：23

作者：

Dehkordi, Mohammad Naderi ^{[1
]}

Badie, Kambiz ^{[2
]}

Zadeh, Ahmad Khadem ^{[2
]}

机构：

[1] Science and Research Branch, Islamic Azad University (IAU), Department of Computer Engineering, Tehran

[2] Iran Telecom Research Center, Tehran

来源：

Journal of Software | 2009年 / 4卷 / 06期

关键词：

Data mining; Genetic algorithms; Privacy preserving; Sensitive association rules;

D O I：

10.4304/jsw.4.6.555-562

中图分类号：

学科分类号：

摘要：

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. © 2009 ACADEMY PUBLISHER.

引用

页码：555 / 562

页数：7

共 15 条

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