Intrusion Detection System Based on Machine Learning Algorithms: A Review

Abstract

Due to the widespread use of the internet, computer networks are vulnerable to cyber-attacks, prompting various researchers to suggest intrusion detection systems (IDSs). Detecting intrusions is one of the important research topics in network security. As a precaution to guarantee the network's security, it aids in the detection of unwanted usage and assaults. This study summarizes significant literature reviews on machine learning (ML), and deep learning (DL) approaches for intrusion detection network analysis and includes a brief instructional overview of each ML / DL method. The papers describing each approach were indexed and summarized according to the dataset used, and the highest level of accuracy was attained.