The rapid evolution and rollout of the digital-enabled intelligent Industrial Internet of Things (IIoT) bring significant opportunities to enterprises. Nevertheless, it has also brought security challenges to network infrastructure. To address the increasing complexity of network security threats, this article uses the edge cloud computing (ECC) to have the edge, which may articulate the premise that the complexity of the network security environment has been significantly increased. This architectural model utilizes the distributed computing power and data locality of edge nodes to deploy network security monitoring and data analysis tasks closer to the edge nodes connecting to the IoT devices. This study uses the distributed computing power and data locality of edge nodes to deploy network security monitoring and data analysis tasks closer to the edge nodes connecting to the IoT devices. By utilizing machine learning and artificial intelligence algorithms, ECC can achieve automated incident detection and response, while additionally using the real-time data processing and analysis technologies to enhance the system’s real-time response capability. Considering throughput, the ECC-based IIoT network security incident detection and response system shows significant advantages. The system has shown significant advantages in terms of throughput because ECC can effectively handle a large number of data streams and has improved its concurrency processing capabilities.