Hybrid cyber threats detection using explainable AI in Industrial IoT

The rise of new technologies have enabled the combination of multiple cyber threats to become more sophisticated and capable cyber attacks, which can result in significant losses and consequences. This work aims to develop a hybrid threats detection systems using explainable artificial intelligence techniques, preventing the growing number of combined cyber attacks in IoT environment. A multilayer hybrid cyber threats model was proposed to analyse increasingly complicated and capable cyber attacks. Meanwhile, an explainable artificial intelligence (XAI) model was designed to create understanble interpretation for the detection model. The experimental results demonstrate the effectiveness of proposed hybrid cyber threats analysis model and XAI model.