부산대학교 도서관

With the continuous integration of information technology and operation technology, the Industrial Internet of Things (IIoT) is gradually changing from closed to open. Operators can configure, monitor, or control the industrial production process remotely via Internet, which brings security threats to IIoTs. Since the IIoT focuses on the availability of industrial production, it is unfeasible to study security issues directly on the industrial field. Thus, constructing an IIoT cyber range to reproduce industrial scenarios for offensive and defensive confrontation research is necessary. However, the traditional IIoT cyber range relies on physical industrial field devices that are not reproducible and hard to recover from cyber-attacks. To solve these problems, in this article, we propose a framework for a digital twin-based cyber range and a digital twin construction method with multiple models. Cyber ranges with digital twins are more flexible and convenient. Based on the proposed method, an industrial scenario is reproduced using machine learning algorithms to predict temperature changes from different perspectives. The experimental result shows the ability of digital twins to construct an IIoT cyber range to reproduce production processes and replace field devices.