An Approach for intrusion detection using machine learning algorithms

Abstract

Individuals and organizations face threats from attackers that constantly attempt to collect information by exploiting their vulnerabilities and obtain unauthorized access to the network. One way of protecting the system is by using an Intrusion detection System (IDS) alongside other security measures like firewalls, antivirus software, and access controls. An intrusion detection system, which is a system that can detect and recognize attacks on a network, is an approach that has been tried, tested, and tweaked to detect attacks as effectively as possible. Therefore, in this work, we will propose an approach using either a feature extraction method or a feature selection algorithm and other machine learning algorithms to provide a new way of intrusion detection, this approach will be applied to the NSL KDD data set.