THE ROLE OF ARTIFICIAL INTELLIGENCE IN PREDICTIVE CYBER THREAT DETECTION AND MITIGATION

Abstract

The rapid evolution of digital infrastructures has led to an increase in the frequency and complexity of cyber threats, posing significant challenges for traditional security systems. In this context, Artificial Intelligence (AI) has emerged as a powerful tool for predictive cyber threat detection and mitigation. By leveraging machine learning, deep learning, and data analytics, AI systems can analyze large volumes of network traffic, user behavior patterns, and historical attack data to identify vulnerabilities, detect anomalies, and predict potential threats before they manifest. AI algorithms continuously improve through iterative learning, adapting to emerging threat landscapes, and providing proactive defenses against cyberattacks. This paper explores the role of AI in enhancing cyber threat detection capabilities, focusing on the integration of predictive models for threat identification, the automation of response mechanisms, and the potential benefits and limitations of AI-based security solutions. Through case studies and analysis, we highlight the efficacy of AI-driven tools in improving the efficiency and accuracy of cybersecurity frameworks while addressing challenges related to data privacy, system integration, and resource allocation.