IRJMST Vol 13 Issue 12 [Year 2022] ISSN 2250 – 1959 (0nline) 2348 – 9367 (Print) International Research Journal of Management Science & Technology http://www.irjmst.com Page 101 Big Data Analytics in Cyber Security Mrs. Preeti Rani Assistant Professor of Computer Science Kanya Mahavidyalaya, Kharkhoda ABSTRACT The ability to compile enormous volumes of digital data, analyze it, visualize it, and derive insights that can help forecast and thwart cyber attacks is known as big data analytics in security. It improves our cyber defence posture together with security technology. They make it possible for businesses to identify patterns of behaviour that indicate network dangers. We concentrate on how Big Data can enhance information security best practises in this article. Keywords: Big Data, Cyber Security, Privacy, Database INTRODUCTION Big Data is a term used to describe data sets that are so massive or complicated that typical data set processing application software is insufficient for or unable to handle them. Big data differs significantly from conventional data in terms of volume, velocity, and variation. Volume denotes the quantity of data generated, Velocity the rate at which the data is produced, and Variation the categories of organized and unstructured data. Big data is now a hot topic for research across practically all disciplines, especially cyber security. Social media websites and mobile devices are the primary sources of this data creation. Since data is being generated at such a rapid rate, many people are concerned about the security of the newly created data. It is crucial to keep this data secure since it contains critical information like credit card numbers and bank account numbers. Additionally, improvements in big data analytics offer ways to collect and use this data, making privacy infractions simpler. As a result, in addition to creating Big Data technologies, it is essential to prevent abuse. DEFINING AND ANALYTICS BIG DATA Massive amounts of data that are exchanged and stored in computer systems are referred to as "big data." Big Data is differentiated from traditional technology in 3 ways: 1. The amount of data (Volume) - Size: The volume of datasets, or how much data has been generated, is an important element. 2. The speed at which data is generated and transmitted (Velocity). The structure, behaviour, and permutations of datasets have a crucial role in complexity. 3. The different categories of organised and unstructured data (Variety). Technologies: the methods and instruments applied to handle large or complicated datasets are an important consideration. TECHNOLOGY MEGA TRENDS Along with analytics and cloud-based technology, big data is receiving a tonne of attention from industry, the media, and even consumers. All of them are a component of the contemporary eco-system that technology megatrends have produced.