SAI-Powered Intrusion Detection Systems: Enhancing Real-Time Network Threat Monitoring – A Systematic Review

Thabet Karkar & Associate Professor Adnan Hadi Al-Helali
Corresponding Author Email: Tlhabet.k@outlook.com

Abstract

Network security is paramount as modern IT infrastructures face increasingly sophisticated threats. Traditional Intrusion Detection Systems (IDS) struggle to cope with evolving attack patterns and high-speed network traffic. Artificial Intelligence (AI) has emerged as a transformative force, enabling real-time, adaptable, and accurate intrusion detection. This systematic review explores the state-of-the-art applications of AI in IDS, with a focus on real-time threat monitoring. We analyze methodologies including machine learning, deep learning, and hybrid approaches, discuss current challenges, and present future directions.

Keywords: Intrusion Detection Systems, Artificial Intelligence, Real-Time Monitoring, Network Security, Machine Learning