Anonymization by Data Relocation using Sub-clustering for Privacy Preserving Data Mining

V  Rajalakshmi   and G  S  Anandha Mala

doi:10.17485/ijst/2014/v7i7.17

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Anonymization by Data Relocation using Sub-clustering for Privacy Preserving Data Mining

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2014/v7i7.17

Year: 2014, Volume: 7, Issue: 7, Pages: 975-980

Original Article

Anonymization by Data Relocation using Sub-clustering for Privacy Preserving Data Mining

V. Rajalakshmi^1* and G. S. Anandha Mala²

1 Sathyabama University, Chennai, Tamil Nadu, India; [email protected]
2 Department of Computer Science and Engineering, St. Joseph’s College of Engineering, Chennai, Tamil Nadu, India; [email protected]

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

As there are new techniques growing to reveal the hidden information on data, the threat towards those data also increases. Therefore, privacy preservation in data mining is an emerging research area which develops various algorithms to anonymize the data provided for data mining. The existing methodology handles the tradeoff between utility and privacy of data in a more expensive way in terms of execution time. In this paper, a simple Anonymization technique using subclustering is specified which achieves maximum privacy and also utility with minimum execution time. The methodology is explained with algorithm and the results are compared with the baseline method.

Keywords: Anonymization, Clustering, Isometric Transformation, Privacy Preservation