iCyberGuard: A FlipIt Game for Enhanced Cybersecurity in IIoT

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.

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Publication Details

Journal
IEEE Transactions on Computational Social Systems
Published
2024-09-16
DOI
https://doi.org/10.1109/tcss.2024.3443174
Citations
8
Primary Topic
Information and Cyber Security
Type
article
Field-Weighted Citation Impact
6.23
Controls
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article

iCyberGuard: A FlipIt Game for Enhanced Cybersecurity in IIoT

Jinpeng Han, Lili Chen, Zhen Wang, Xiaoguang Chen et al.
8 citations
IEEE Transactions on Computational Social Systems
Information and Cyber Security
6.23
article

iCyberGuard: A FlipIt Game for Enhanced Cybersecurity in IIoT

Jinpeng Han, Lili Chen, Zhen Wang, Xiaoguang Chen, Manzhi Yang, Wenyuan Cao, Fei‐Yue Wang
article en
8 citations

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.

IEEE Transactions on Computational Social SystemsVol. 11(6)
Macau University of Science and Technology (MO), Chinese Academy of Sciences (CN), Hangzhou Dianzi University (CN), Xi'an Jiaotong University (CN)
Openalex Percentile: Top 3%
Information and Cyber Security
6.23
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iCyberGuard: A FlipIt Game for Enhanced Cybersecurity in IIoT — Jinpeng Han, Lili Chen, et al. · IEEE Transactions on Computational Social Systems (2024) | TGRS Research Map | TGRS