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Approaches for Privacy Preserving Data Mining by Various Associations Rule Hiding Algorithms – A Survey
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 134 - Number 11 |
| Year of Publication: 2016 |
| Authors: Umesh Kumar Sahu, Anju Singh |
10.5120/ijca2016908042
|
Umesh Kumar Sahu, Anju Singh . Approaches for Privacy Preserving Data Mining by Various Associations Rule Hiding Algorithms – A Survey. International Journal of Computer Applications. 134, 11 ( January 2016), 21-26. DOI=10.5120/ijca2016908042
Abstract
Yesteryears, data mining has emerged as a very popular tool for extracting hidden knowledge from collection of huge amount of data. Major challenges of data mining are to find the hidden knowledge in the data while the sensitive information is not revealed. Many Industry ,Defence ,Public Sector and Organisation facing risk or having security issue while sharing their data so it is very crucial concern how to protect their sensitive information due to legal and customer concern. Many strategies have been proposed to hide the information containing sensitive data. Privacy preserving data mining is an answer to such problems. Association rule hiding is one of the PPDM techniques to protect the sensitive association rule .In this paper, all the approaches for privacy preserving data mining have been compared theoretically and points out their pros and cons.
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