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     Research Journal of Applied Sciences, Engineering and Technology


State-of-the-art in Privacy Preserved K-anonymity Revisited

1,2Yousra Abdul Alsahib S. Aldeen and 1Mazleena Salleh
1Faculty of Computing, Universiti Teknologi Malaysia, UTM, 81310 UTM Skudai, Johor, Malaysia
2Department of Computer Science, College of Education_Ibn Rushd, Baghdad University, Baghdad, Iraq
Research Journal of Applied Sciences, Engineering and Technology  2016  7:782-789
http://dx.doi.org/10.19026/rjaset.12.2753  |  © The Author(s) 2016
Received: November ‎3, ‎2015  |  Accepted: January ‎8, ‎2016  |  Published: April 05, 2016

Abstract

The prevalent conditions in data sharing and mining have necessitated the release and revelation of certain vulnerable private information. Thus the preservation of privacy has become an eminent field of study in data security. In addressing this issue, K-anonymity is amongst the most reliable and valid algorithms used for privacy preservation in data mining. It is ubiquitously used in myriads of fields in recent years for its characteristic effective prevention ability towards the loss of vulnerable information under linking attacks. This study presents the basic notions and deep-insight of the existing privacy preserved K-anonymity model and its possible enhancement. Furthermore, the present challenges, excitements and future progression of privacy preservation in K-anonymity are emphasized. Moreover, this study is grounded on the fundamental ideas and concepts of the existing K-anonymity privacy preservation, K-anonymity model and enhanced the K-anonymity model. Finally, it extracted the developmental direction of privacy preservation in K-anonymity.

Keywords:

Generalization, privacy preservation, suppression and Quasi Identifiers (QI),


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Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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