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A Survey on Privacy Preserving Data Mining Techniques

Author(s):

Hetal Shah , Vadodara Institue of Engineering

Keywords:

Data Mining, Privacy Preserving, Randomization, Suppression, K-Annoymity

Abstract

Data mining is a process of extracting useful knowledge and an important data from large data sets. The typical process of data collection and data dissemination result in a possible risk of privacy threats and attacks. Some private information about individuals, businesses and organizations has to be suppressed before it is shared or published. In recent years, privacy preserving data mining (PPDM) has been studied extensively, because of the wide proliferation of sensitive information on the internet. Privacy preserving data mining has become increasingly popular because it allows sharing of privacy sensitive data for analysis purposes. It is essential to maintain a ratio between privacy protection and knowledge discovery. The primary goal of this survey paper is to understand the existing privacy preserving data mining techniques and to achieve efficiency.

Other Details

Paper ID: IJSRDV4I110057
Published in: Volume : 4, Issue : 11
Publication Date: 01/02/2017
Page(s): 145-147

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