An Efficient Data Mining Method for Clustering on Privacy Preserving Concept |
Author(s): |
| Bhuvaneswari T , SANKARA COLLEGE OF COMMERCE AND SCIENCE; Sasikala R, SANKARA COLLEGE OF COMMERCE AND SCIENCE |
Keywords: |
| Data mining, privacy preserving, Clustering |
Abstract |
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Privacy preserving data mining has become increasingly popular because it allows sharing of private sensitive data for analysis purposes. The concept of privacy preserving data mining has been proposed in response to these privacy concerns. The main goal of this research work has introduced a new k-Anonymity algorithm which is capable of transforming a non anonymous data set into a k-Anonymity data set. K-Anonymity model is thus to transform a table so that no one can make high-probability associations between records in the table and the corresponding entities. In order to achieve this goal, the K-Anonymity model requires that any record in a table be indistinguishable from at least (k−1) other records with respect to the pre-determined quasi-identifier. Finally the modified dataset is used for clustering. |
Other Details |
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Paper ID: IJSRDV5I10020 Published in: Volume : 5, Issue : 1 Publication Date: 01/04/2017 Page(s): 8-12 |
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