AI-Based Threat Detection: A Modern Approach to Cybersecurity

Abstract

The increasing complexity and frequency of cyberattacks demand proactive and intelligent threat detection systems. Traditional signature-based detection methods are insufficient to handle sophisticated threats like zero-day attacks and advanced persistent threats (APTs). This paper explores AI-based threat detection systems that leverage machine learning (ML), deep learning (DL), and natural language processing (NLP) to analyze large volumes of data, recognize patterns, and detect anomalies. We review various AI techniques, real-world applications, case studies, benefits, challenges, and future directions in this emerging field.