PREDICTIVE ANALYTICS FOR CYBER THREATS: ENHANCING PROACTIVE DEFENSE MECHANISMS
Niranjan Reddy Kotha · INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & TECHNOLOGY · 2022
In the dynamic landscape of cybersecurity, organizations face an ever-evolving array of cyber threats that necessitate proactive defense strategies.Predictive analytics, leveraging advanced statistical methods, machine learning (ML), and artificial intelligence (AI), offers significant potential in anticipating and mitigating cyber threats before they materialize.This paper provides a comprehensive examination of predictive analytics in the context of cybersecurity, detailing its core methodologies, applications, and the benefits it brings to threat detection and prevention.Through an extensive literature review and analysis of recent case studies, we assess the effectiveness of predictive analytics in identifying emerging threats, enhancing incident response, and reducing the impact of cyberattacks.The study also explores the challenges associated with implementing predictive analytics, including data quality, model accuracy, and integration with existing security frameworks.Future research directions are proposed to address these challenges, emphasizing the need for more sophisticated models, improved data integration techniques, and collaborative threat intelligence sharing.The findings underscore the critical role of predictive analytics in fortifying organizational defenses and fostering a proactive cybersecurity posture.