ROSE-BOX: An Approach for Intrusion Detection in Industrial Internet of Things

With the rapid development of industrial network, Industrial Internet of Things (IIoT) has become an indispensable part of industrial network development. However, due to the vulnerability of Industrial Internet of Things to network intrusion attacks. Therefore, anomaly detection in IIoT is particularly important. In this paper, an effective intrusion detection approach ROSE-BOX (Random fOrest, SmotE, BO-Xgboost) is proposed to detect multi-class cyberattacks based on Random Forest, SMOTE and BO-XGBoost in IIoT. It is worth mentioning that BO-XGBoost is obtained by optimizing the parameters of XGBoost using Bayesian optimization. Finally, compared with other existing methods, the proposed approach has better detection performance, with an accuracy rate of over 99.85%.