ENHANCING CYBER SECURITY THROUGH MACHINE LEARNING BASED ON BIG DATA ANALYTICS

Abstract

Over 5.35 billion people used the Internet in 2024, and the data generated exceeded 147ZB by the end of 2024. This rapid increase in data generation has pushed big data applications to new heights. Intelligent information investigation methods are required for mining, translating, and visualising data when diverse gadgets and sources collect or produce an extensive information collection. This paper investigates the crossing point of vast amounts of Information and cybersecurity, highlighting the essential part of analytics in identifying. This paper gives bits of knowledge into the current state of Big Data analytics for cybersecurity through a comprehensive survey of existing literature, case studies, and innovative approaches. It traces future bearings for investigation and development. The union of cutting-edge innovations, coupled with a proactive and versatile approach, builds up Enormous Information analytics as a cornerstone in fortifying the digital landscape against an evolving spectrum of cyber threats. Ultimately, this research contributes to the ongoing discourse on bolstering cybersecurity measures in an ever-evolving and dynamic threat landscape.