Unmasking Insider Threats: How Big Data Analytics is Revolutionizing Cybersecurity Defense
International Research Journal of Modernization in Engineering Technology and Science · 2025
Organizations face growing difficulty because insider threats emerge from workers and trusted personnel who maintain authorized access to sensitive systems together with crucial information.Standard security measures show limited effectiveness in identifying threats made by internal personnel because internal threats prove harder to detect than external ones.Organizations now use big data analytics as an effective transformative solution to both detect and stop and react to insider threats.Live big data analysis enables tools to identify abnormal conduct that signals potential threats before they emerge from large sets of data.Artificial intelligence together with machine learning capabilities help this procedure through continuous improvement of abnormal activity detection from historical data analysis.As the main subject of this research is to demonstrate how big data analytics transforms cybersecurity defense through enhanced threat recognition alongside reduced alert flase rates and comprehensive security system fortification of organizations.