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The widespread deployment of the Internet of Things (IoT) into critical sectors such as industrial and manufacturing has resulted in the Industrial Internet of Things (IIoT). The IIoT consists of sensors, actuators, and smart devices that communicate with one another to optimize manufacturing and industrial processes. Although IIoT provides various benefits to both service providers and consumers, security and privacy remain a big challenge. An intrusion detection system (IDS) has been utilized to mitigate cyberattacks in such a connected network. However, many existing solutions for IDS in IIoT suffer from the lack of comprehensiveness of the types of attack the network is exposed to, high feature dimension, models built on out-of-date datasets, and a lack of focus on the problem of imbalanced datasets. To address the aforementioned issues, we propose an intelligent detection system for identifying cyberattacks in …