Predictive Analytics for Cybersecurity Threat Detection and Intelligent Incident Response in Next-Generation Digital Infrastructures

Abstract

In the modern era of rapid digital transformation, cybersecurity has emerged as one of the most critical challenges for individuals, organizations, and governments. The exponential growth of data, cloud computing, Internet of Things (IoT), and artificial intelligence (AI) has significantly expanded the attack surface for malicious actors. Predictive analytics offers a transformative solution for proactive threat detection, mitigation, and response by harnessing the power of big data analytics, machine learning (ML), and artificial intelligence. This paper explores the role of predictive analytics in cybersecurity, focusing on its methodologies, frameworks, challenges, and applications for intelligent threat detection and incident response. It also discusses recent developments, the integration of explainable AI (XAI), and the future scope of predictive analytics-driven cybersecurity in next-generation digital infrastructures.

KEYWORDS: Predictive Analytics, Cybersecurity, Threat Detection, Machine Learning, Artificial Intelligence, Big Data, Incident Response, Anomaly Detection, Explainable AI