Big Data Security Issues and Challenges

Abstract

Every day, the amount of data on the globe increases. Big data a word used to describe a vast array of sets of data that are very big and complicated that has recently become common, is facing significant security and privacy issues. Conventional privacy and security systems are inefficient and unable to keep up with the fast pace environment development of data in such a dynamic distributed computing system because of big data's shared characteristics, including volume, variety, and velocity related to the increased public cloud as well as the Internet of Things (IoT). As information technology is widely employed for decision-making by businesses and governments throughout the world, security risk minimization is becoming more critical in big data infrastructure and services. Modern security systems have been unable to keep up using today's technology's flexibility, scalability, and adaptation, which are essential for large data. To fill that void in the literature, this article represents an experimental first step to use first concepts. To start, we define the latest trends in big data in a detailed manner defining eleven Vs as significant aspects of data mining that contribute to the imminent security issue. Next, to uncover the key privacy and security challenges of data analytics, the eleven Vs are used to represent the three stages of the big information life cycle. Finally, presents the literature review of securing and protecting huge data challenges with emphasis on the distinguishing features of Big Data. This thesis will pave the way for further studies into this crucial area of big data protection.

Keywords

• big data
• privacy issues
• security risks
• exabyte’s
• data analytics