Review of Intrusion Detection System for Prediction of Cyber Attacks using AI Techniques

Abstract

The ever-evolving threat landscape of cyber-attacks necessitates continuous advancements in intrusion detection systems (IDS). This paper delves into the application of Artificial Intelligence (AI) techniques to enhance the predictive capabilities of IDS. We explore the limitations of traditional signature-based and anomaly-based IDS approaches and highlight the potential of AI methods like machine learning (ML) and deep learning (DL) for identifying and predicting novel and sophisticated cyber-attacks. By integrating AI into IDS, organizations can bolster their cyber security posture, proactively mitigate threats, and safeguard their critical infrastructure.