Dual-IDS: A bagging-based gradient boosting decision tree model for network anomaly intrusion detection system

Maya Hilda Lestari Louk, Bayu Adhi Tama

Abstract: Highlights•A dual ensemble model is proposed for anomaly-based intrusion detection system.•Bagging-GBM performs the best in comparison to other existing models.•Multiple intrusion data sets are used to validate the proposed model.