Intrusion Detection System in the Industrial Internet of Things (IIoT) Using Deep Learning

The rapid development of Industrial Internet of Things (IIoT) solutions made the industrial networks more vulnerable to different kinds of cyberattacks. Intrusion detection systems are key security controls in these systems. Traditional intrusion detection approaches often struggle to keep pace with the dynamic and complex nature of IIoT networks. This paper presents intrusion detection solutions based on deep learning methods focusing on DNN and CNN models on Edge-IIoTset Dataset. The evaluation of those models is done with different metrics (loss, accuracy, etc.). The experimental results showed that the performances of the deep learning approaches outperformed traditional intrusion detection system.