High Impact Factor : 4.396 icon | Submit Manuscript Online icon |

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

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

Paper ID: IJSRDV5I10020
Published in: Volume : 5, Issue : 1
Publication Date: 01/04/2017
Page(s): 8-12

Article Preview

Download Article