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ISSN: 2321-9939 | ESTD Year: 2013

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Paper Title
Big data privacy methods
Authors
  Meenal Sankhla,  Avani Kothari,  Akshay Khandelwal,  Himanshi Solanki,  Jayesh Surana

Abstract
Big data is a term used for large and complex data sets that cannot be stored and processed using traditional data processing software. Since, big data require high computational power and storage, distributed system are used. Big data Analytics is a term used for deriving some meaningful and hidden data from the large data sets. The data sets are collected from social media, healthcare centers, data governance, institutions, etc. Thus, privacy and security of the data become the prime concern. This paper focus on the privacy and security concerns and the problems in the privacy of big data. The privacy in big data is divided into three stages-data generation, data storage and data processing. This paper also covers some traditional methods adopted for privacy in big data, the challenges faced by these techniques. The goal of this paper is to study the recent techniques adopted for privacy and draw their comparison in order to declare the most efficient technique among all of them.

Keywords- Big data Privacy and security Privacy preserving: k-anonymity: T-closeness, L-diversity, De-identification
Publication Details
Unique Identification Number - IJEDR1702165
Page Number(s) - 979-983
Pubished in - Volume 5 | Issue 2 | May 2017
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Meenal Sankhla,  Avani Kothari,  Akshay Khandelwal,  Himanshi Solanki,  Jayesh Surana,   "Big data privacy methods", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.5, Issue 2, pp.979-983, May 2017, Available at :http://www.ijedr.org/papers/IJEDR1702165.pdf
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