Intrusions Detecting in Network Systems using Data Mining Techniques

Abstract

The intrusion detection system is one of the most important security parameters of modern computer networks, which will be able to detect intrusions in the network by examining the series of different events. The system is used independently in the network and can detect the occurrence of an attack based on two abnormal behavior detection techniques. Currently, most research has been conducted on infiltration detection systems in the field of unusual behavior-based detection using various techniques (statistical, artificial intelligence, data mining, machine learning). The study used an improved ant colony algorithm to detect Trojan malware. The study used a KDD dataset with an accuracy rate of 96.33.