iCyberGuard: A FlipIt Game for Enhanced Cybersecurity in IIoT

Xiaoguang Chen, Wenyuan Cao, Lili Chen, Jinpeng Han, Manzhi Yang, Zhen Wang, Fei-Yue Wang

Abstract: Social manufacturing has significantly advanced the industrial Internet of Things (IIoT), integrating information technology and operation technology to enhance production efficiency and quality, and to foster new business models. This integration, however, introduces novel risks, including advanced persistent threats, which demand robust security measures to safeguard IIoT systems. This article proposes an iCyberGuard game model, tailored for IIoT environments, designed to imitate the cyber and physical attacks for information and operation technologies. Then, we used a reinforcement learning algorithm to compute the optimal strategy. We conducted comprehensive simulation experiments, which demonstrate that our model the strategic interactions between attackers and defenders. Participants are enabled to learn adaptively, discerning optimal strategies based on the intelligence of their adversaries. Finally, we explain the practical significance of the best strategy of defenders or attackers, and how users can rely on these best strategies to strengthen the security performance of the network.