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The Effect of Key Nodes on the Malware Dynamics in the Industrial Control Network

Qiang Fu1, Jun Wang1,*, Changfu Si1, Jiawei Liu2

1 College of Computer Science and Technology, Shenyang University of Chemical Technology, Shenyang, 110142, China
2 College of Computer Science and Engineering, Northeastern University, Shenyang, 110169, China

* Corresponding Author: Jun Wang. Email: email

(This article belongs to the Special Issue: Recent Advances in Ensemble Framework of Meta-heuristics and Machine Learning: Methods and Applications)

Computers, Materials & Continua 2024, 79(1), 329-349. https://doi.org/10.32604/cmc.2024.048117

Abstract

As industrialization and informatization become more deeply intertwined, industrial control networks have entered an era of intelligence. The connection between industrial control networks and the external internet is becoming increasingly close, which leads to frequent security accidents. This paper proposes a model for the industrial control network. It includes a malware containment strategy that integrates intrusion detection, quarantine, and monitoring. Based on this model, the role of key nodes in the spread of malware is studied, a comparison experiment is conducted to validate the impact of the containment strategy. In addition, the dynamic behavior of the model is analyzed, the basic reproduction number is computed, and the disease-free and endemic equilibrium of the model is also obtained by the basic reproduction number. Moreover, through simulation experiments, the effectiveness of the containment strategy is validated, the influence of the relevant parameters is analyzed, and the containment strategy is optimized. In other words, selective immunity to key nodes can effectively suppress the spread of malware and maintain the stability of industrial control systems. The earlier the immunization of key nodes, the better. Once the time exceeds the threshold, immunizing key nodes is almost ineffective. The analysis provides a better way to contain the malware in the industrial control network.

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APA Style
Fu, Q., Wang, J., Si, C., Liu, J. (2024). The effect of key nodes on the malware dynamics in the industrial control network. Computers, Materials & Continua, 79(1), 329-349. https://doi.org/10.32604/cmc.2024.048117
Vancouver Style
Fu Q, Wang J, Si C, Liu J. The effect of key nodes on the malware dynamics in the industrial control network. Comput Mater Contin. 2024;79(1):329-349 https://doi.org/10.32604/cmc.2024.048117
IEEE Style
Q. Fu, J. Wang, C. Si, and J. Liu "The Effect of Key Nodes on the Malware Dynamics in the Industrial Control Network," Comput. Mater. Contin., vol. 79, no. 1, pp. 329-349. 2024. https://doi.org/10.32604/cmc.2024.048117



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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