Privacy preserving method for knowledge discovered by data mining

被引：0

作者：

Tedmori S. ^{[1
]}

机构：

[1] Department of Computer Science, King Hussein Faculty of Computing Sciences, Princess Sumaya University for Technology, P.O. Box 1438, Amman

来源：

International Journal of Information and Communication Technology | 2019年 / 14卷 / 01期

关键词：

Data engineering; Data mining; Discovering knowledge; Privacy preserving;

D O I：

10.1504/IJICT.2019.096598

中图分类号：

学科分类号：

摘要：

In spite of its success in a wide variety of applications, data mining technology raises a variety of ethical concerns which include among others privacy, intellectual property rights, and data security. In this paper, the author focuses on the privacy problem of unauthorised use of information obtained from knowledge discovered by secondary usage of data in clustering analysis. To address this problem, the author proposes the use of a combination of isometric data transformation methods as an approach to guarantee that data mining does not breach privacy. The three transformation methods of reflection, rotation, and translation are used to distort confidential numerical attributes for the purposes of satisfying the privacy requirements, while maintaining the general features of the cluster in clustering analysis. Experimental results show that the proposed algorithm is effective and provide acceptable values for balancing privacy and accuracy. © 2019 Inderscience Enterprises Ltd.

引用

页码：31 / 45

页数：14

共 40 条

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