Authors: Sara Tedmori
Addresses: Department of Computer Science, King Hussein Faculty of Computing Sciences, Princess Sumaya University for Technology, P.O. Box 1438 Amman 11941, Jordan
Abstract: 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.
Keywords: privacy preserving; data mining; discovering knowledge; data engineering.
International Journal of Information and Communication Technology, 2019 Vol.14 No.1, pp.31 - 45
Available online: 25 Oct 2018 *Full-text access for editors Access for subscribers Free access Comment on this article