Network Intrusion Detection using a Hybridized Harmony Search and Random Forest

Abstract

Intrusion Detection Systems are used to find security holes in a system. However, a number of factors, including irrelevant information, contribute to intrusion detection system's low detection accuracy. This work presents a hybrid intrusion detection system (IDS) that combines the Random Forest algorithm and Harmony Search to address this issue and increase IDS detection accuracy. The proposed method was analyzed using NSL-KDD, and the experiment results show that the model functions effectively.