Intelligent intrusion Detection of computer networks using Random Forest Algorithm

Abstract

Intelligent intrusion detection systems are one of the important research fields in computer network security. The purpose of the intrusion detection system is to detect and identify attacks and detect security problems in computer systems and networks and notify security managers. The main algorithm used in this article is the random forest algorithm. To check the effectiveness of the proposed algorithm in intelligent intrusion detection, the NSL-KDD dataset has been used, which includes 125,973 samples and has 41 features. Since the random forest algorithm is a hybrid algorithm and is created from several decision trees, it achieves high accuracy in intelligent intrusion detection. By using this algorithm, we were able to increase the accuracy of intelligent intrusion detection by 99.89%.