Privacy Protection in Bigdata: A Survey

Saumya Gupta, Et Al

doi:10.17762/turcomat.v12i2.888

Abstract

Bigdata becomes a significant sector and academics research topic. Bigdata is a two-edged sword. The rising volume of information together will increase the likelihood of blundering non-public data privacy. Due to many new technologies and innovations that pervade our everyday lives, like smartphones and social networking apps, and the Internet of Things-based intelligent-world systems, the large amount of data generated in our world has exploded. During this data processing, storage, and the use of the information it can quickly cause personal information exposure and the difficulty of interpreting the information. The aim is to incorporate this range of information into one framework for big data management and to recognize problems regarding privacy. This paper begins with the introduction of bigdata, its process, protection issues, and tools which are used to solve its problems

Highlights

Bigdata relates to the bulk of data that came from dissimilar data originators and have, unlike formats
Continuous increase of data is captured from IoT such as RIFD, remote sensing, software logs, microphones, wireless sensor network, and many more, which generate large and complex data set in huge volume, the information could be organized, semiorganized and unstructured for that customary applications for information preparing are insufficient [2] [11]
A. (2012) discuss, many Hadoop MapReduce analysis methods can be utilized to improve the presentation by an equivalent amount. We demonstrate these methods throughout this review

Summary

Introduction

Bigdata relates to the bulk of data that came from dissimilar data originators and have, unlike formats. In [4], this concept is referred to as Bigdata “youth of today of techniques and structures aimed at generating, investigating, and analyzing heavy-volume information from very broad quantities of data”. This definition illustrates the 3V-volume, velocity, and variety characteristics or template of big data. Refers to data b eing generated i s not a single ca tegory, and the data systems ar e complex. This refers to the rate of producing, processing, and analyzing huge amounts of data. Refers to the importance of the study of BigData and data's economic value

Trustworthiness Availability Accountability Authenticity Reputation

Big data Storag a Processin g

Findings

Conclusion