NDLI: A Novel Method for Preserving Privacy in Big-Data Mining

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A Novel Method for Preserving Privacy in Big-Data Mining

Content Provider	Semantic Scholar
Author	Hussain, Nasrin Irshad Choudhury, Bharadwaj Rakshit, Sandip
Copyright Year	2014
Abstract	our daily lives has become digitization which led to an explosion in the collection of data by organization and individuals. Organization push their vast amount of data into big data clusters, but most have implemented zero security measures. Protection on confidentiality of these data is very important. In recent years privacy-preserving data mining has been emerged as a popular research area for the security of sensitive information in the network. In this field we study the extraction of knowledge or pattern from big data maintaining the commercial or legislative privacy constraints. Privacy preserving mining of distributed data has diverse applications. We have numerous algorithmic techniques for privacy preserving data mining.This paper presents a privacy preserving method for big data. We proposed a novel method for preserving privacy in mining big databases. Our goal is to mining the data while preserving data privacy and confidentiality.
Starting Page	21
Ending Page	25
Page Count	5
File Format	PDF HTM / HTML
DOI	10.5120/18159-9378
Volume Number	103
Alternate Webpage(s)	https://www.ijcaonline.org/archives/volume103/number16/18159-9378?format=pdf
Alternate Webpage(s)	https://doi.org/10.5120/18159-9378
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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