Optimal control analysis of malware propagation in cloud environments

Liang Tian; Fengjun Shang; Chenquan Gan; Liang Tian; Fengjun Shang; Chenquan Gan

doi:10.3934/mbe.2023649

Mathematical Biosciences and Engineering

2023, Volume 20, Issue 8: 14502-14517. doi: 10.3934/mbe.2023649

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Optimal control analysis of malware propagation in cloud environments

1.
School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2.
Key Lab of Computer Network and Communication Technology, Chongqing Education Commission, Chongqing, China
3.
School of Cyber Security and Information Law, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Academic Editor: Ángel Martín del Rey

Received: 31 March 2023 Revised: 25 May 2023 Accepted: 06 June 2023 Published: 04 July 2023

Cloud computing has become a widespread technology that delivers a broad range of services across various industries globally. One of the crucial features of cloud infrastructure is virtual machine (VM) migration, which plays a pivotal role in resource allocation flexibility and reducing energy consumption, but it also provides convenience for the fast propagation of malware. To tackle the challenge of curtailing the proliferation of malware in the cloud, this paper proposes an effective strategy based on optimal dynamic immunization using a controlled dynamical model. The objective of the research is to identify the most efficient way of dynamically immunizing the cloud to minimize the spread of malware. To achieve this, we define the control strategy and loss and give the corresponding optimal control problem. The optimal control analysis of the controlled dynamical model is examined theoretically and experimentally. Finally, the theoretical and experimental results both demonstrate that the optimal strategy can minimize the incidence of infections at a reasonable loss.
- cloud environment,
- virtual machine,
- malware,
- propagation model,
- optimal control
Citation: Liang Tian, Fengjun Shang, Chenquan Gan. Optimal control analysis of malware propagation in cloud environments[J]. Mathematical Biosciences and Engineering, 2023, 20(8): 14502-14517. doi: 10.3934/mbe.2023649

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Abstract

Cloud computing has become a widespread technology that delivers a broad range of services across various industries globally. One of the crucial features of cloud infrastructure is virtual machine (VM) migration, which plays a pivotal role in resource allocation flexibility and reducing energy consumption, but it also provides convenience for the fast propagation of malware. To tackle the challenge of curtailing the proliferation of malware in the cloud, this paper proposes an effective strategy based on optimal dynamic immunization using a controlled dynamical model. The objective of the research is to identify the most efficient way of dynamically immunizing the cloud to minimize the spread of malware. To achieve this, we define the control strategy and loss and give the corresponding optimal control problem. The optimal control analysis of the controlled dynamical model is examined theoretically and experimentally. Finally, the theoretical and experimental results both demonstrate that the optimal strategy can minimize the incidence of infections at a reasonable loss.

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