Feature Selection Model Based on Gorilla Troops Optimizer for Intrusion Detection Systems

Cyber security is a fundamental challenge to the Internet of things (IoT) and smart home environments .This paper presents modified method ystem (IDS).setection dntrusion ienhance performance This modification achieved by introducing an alternative feature selection (FS) . ptimizer (GTO) algorithm.oroops torilla gmodel based on Recently, FS has played significant role in increasing detection anomalies IDSs. To evaluate efficiency developed method, set experimental conducted using three datasets, including NSL-KDD, CICIDS2017, Bot-IoT datasets.asresults w xtraction (FE) model reduce dimensions these datasets as first step.Teeature f used areetworks (CNN) neural nonvolutional cThe hen, extracted features are passed for detection. The results compared with well-known IDS technique. show superiority over all other methods according metrics.