AI-Powered Intrusion Detection Systems

Abstract

The increasing frequency and sophistication of cyberattacks have made cybersecurity a critical concern for organizations worldwide. Traditional Intrusion Detection Systems (IDS) rely primarily on signaturebased techniques, which are often ineffective against new and evolving threats. Artificial Intelligence (AI) has emerged as a transformative technology capable of enhancing intrusion detection through intelligent analysis, pattern recognition, and adaptive learning. This paper examines the role of AI in modern intrusion detection systems, highlighting the opportunities it offers in detecting complex cyber threats while addressing the challenges associated with implementation. The study discusses machine learning and deep learning techniques used in IDS, explores their benefits and limitations, and identifies future research directions. The findings suggest that AI-powered IDS can significantly improve cybersecurity resilience when combined with robust data management, explainable models, and continuous monitoring.

Keywords