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Wireless sensor networks (WSNs) are attracting significant interest due to their substantial potential in various applications. The present paper examines the Susceptible-Exposed1-Exposed2-Infectious1-Infectious2-Recovered-Vaccinated (S E \(_1\) E \(_2\) I \(_1\) I \(_2\) RV) model constructed according to the classical SEIRV epidemic model. The original SEIRV model, which includes a vaccination compartment, offers a structure for precisely capturing the spatial and temporal dynamics of the process of malware propagation. In the SE \(_1\) E \(_2\) I \(_1\) I \(_2\) RV model, two distinct exposed and infected states are considered due to the assumption of two types of malware attacks, specifically worms and viruses, within the network. The considered model is based on a system of differential equations. The free equilibrium points and model stability are investigated. The basic reproduction number, a critical parameter for characterizing malware propagation in WSNs, is calculated. Numerical simulations were conducted utilizing Matlab to validate the theoretical analyses.

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Epidemic Analysis of the Propagation of Multiple Malware Infectious in Wireless Sensor Networks

  • 会议论文

  • 发表日期：

    2025年

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  • Leila Moradi,
  • Eslam Farsimadan,
  • Gianni D’Angelo,
  • Bruno Carpentieri,
  • Francesco Palmieri

摘要

Wireless sensor networks (WSNs) are attracting significant interest due to their substantial potential in various applications. The present paper examines the Susceptible-Exposed1-Exposed2-Infectious1-Infectious2-Recovered-Vaccinated (S E \(_1\) E \(_2\) I \(_1\) I \(_2\) RV) model constructed according to the classical SEIRV epidemic model. The original SEIRV model, which includes a vaccination compartment, offers a structure for precisely capturing the spatial and temporal dynamics of the process of malware propagation. In the SE \(_1\) E \(_2\) I \(_1\) I \(_2\) RV model, two distinct exposed and infected states are considered due to the assumption of two types of malware attacks, specifically worms and viruses, within the network. The considered model is based on a system of differential equations. The free equilibrium points and model stability are investigated. The basic reproduction number, a critical parameter for characterizing malware propagation in WSNs, is calculated. Numerical simulations were conducted utilizing Matlab to validate the theoretical analyses.