Exploring and Presenting Security Measures in Big Data Paradigm

Abstract

Big Data is a field that provides different ways to analyze and to extract information and hidden patterns. It also helps to deal with the data sets which are complex and larger in size. In many cases, data offers greater statistical power while the data with higher complexity leads to a higher false discovery rate. At the current time due to the key concepts like volume, variety, and velocity which are associated with Big Data, privacy and security are the biggest challenges in this field. So in this chapter, we have discussed different types of issues and solutions related to security and privacy in Big Data. In the field of Big Data, privacy is the liberty to control how personal information is collected, organized, and used. Whereas security in Big Data refers to the process of protecting information from destructive forces and from the unwanted actions of unauthorized users, such as a cyberattack or a data breach. In this field, privacy and security both are very important issues. The security model of Big Data is not recommended for complex applications and as a result of which by default it gets disabled. But in the absence of this model, the data can be easily compromised. So through this chapter, we have tried to highlight the privacy threats, issues and challenges of Big Data. Several techniques required to maintain data security have also been covered in brief.