An Overview of Big Data Security

Rashi Srivastava*, Tanisha Gahlawat**, Parul Kalra***
* UG Scholar, Department of Information TechnologyAmity School of Technology, Noida, Uttar Pradesh, India.
**-*** Amity School of Technology, Noida, Uttar Pradesh, India.
Periodicity:October - December'2016
DOI : https://doi.org/10.26634/jse.11.2.13445

Abstract

In today's advancing world, data is increasing day by day and due to its vast size it has become very difficult to incorporate security to all the data. Interest in security function of data is increasing due to growth of network technology. It is also increasing with development of cloud computing an area which is rich in source for information along with network traffic. This area needs security. Through this paper, the authors propose an overview of big data security problems, which includes its varieties, and challenges. It also discusses privacy concern on big data. The methodology adopted for protection is attribution selection, that is determined by the background of big data. It is also ascertained by data mining and big data features.

Keywords

Encryption, Analyzing, Tools, Securing Data.

How to Cite this Article?

Srivastava R., , Gahlawat, T., and Kalra, P. (2016). Comparisons of Naive Bayes, Back Propagation, Deep Learning algorithm to Measure the Performance with Make Use of Dataset. i-manager’s Journal on Software Engineering, 11(2), 20-25. https://doi.org/10.26634/jse.11.2.13445

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