Zero-day Virus Transmission Model and Stability Analysis

Qingwei MENG; Mingyang QIU; Gang WANG; Runnian MA

doi:10.11999/JEIT200519

Volume 43 Issue 7

Jul. 2021

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Qingwei MENG, Mingyang QIU, Gang WANG, Runnian MA. Zero-day Virus Transmission Model and Stability Analysis[J]. Journal of Electronics & Information Technology, 2021, 43(7): 1849-1855. doi: 10.11999/JEIT200519

Citation:

Qingwei MENG, Mingyang QIU, Gang WANG, Runnian MA. Zero-day Virus Transmission Model and Stability Analysis[J]. Journal of Electronics & Information Technology, 2021, 43(7): 1849-1855. doi: 10.11999/JEIT200519

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Zero-day Virus Transmission Model and Stability Analysis

doi: 10.11999/JEIT200519

Information and Navigation Institute, Air Force Engineering University, Xi’an 710077, China

Funds: The National Nature Science Foundation of China (61573017)

Received Date: 2020-06-23
Rev Recd Date: 2020-11-26

Available Online: 2020-12-01

Publish Date: 2021-07-10

Abstract

Abstract

According to the characteristics and propagation law of zero-day virus, the propagation model and stability of zero-day virus are studied. Firstly, the mechanism of zero-day virus transmission is analyzed. Based on the Susceptible-Infected-Removed-Susceptible(SIRS) virus transmission model, the node of infection state is redefined, the node of execution state and the node of damage state are introduced, and the zero-day virus transmission Susceptible - Initial-state-of infection- Zero-day - Damaged – Recovery (SIZDR) dynamic model is established. Secondly, the local stability of the system equilibrium point, the basic regeneration number and its influence on the scale of virus transmission are analyzed by using Rous stability criterion. Finally, the local stability of the model is verified by simulation, and the influence of node infection rate, node degree and node damage rate on zero-day virus transmission is analyzed. Theoretical analysis and simulation results show that the proposed model can objectively reflect the law of zero-day virus transmission, and the magnitude of zero-day virus spread is positively correlated with node degree and node infection rate, and negatively correlated with node damage rate. Targeted prevention and control of known viruses can effectively improve the defense effect against zero-day viruses.
- Zero-day attack,
- Virus propagation model,
- Stability

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References(17)

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