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Transmission Dynamics of Computer Virus Propagation Model Through Delay Effect Demonstration

Author

Listed:
  • Ali Raza
  • Eugénio M. Rocha
  • Mohammed Mahyoub Al-Shamiri
  • Nauman Ahmed
  • Muhammad Rafiq
  • Maysaa Elmahi Abd Elwahab
  • Emad Fadhal

Abstract

According to the report of Statista, in 2023, the worldwide number of malware attacks reached 6.06 billion, an increase of 10 percent compared to the preceding year. In recent years, the highest number of malware attacks was detected in 2018, when 10.5 billion such attacks were reported across the globe. In the present study, to analyze the dynamics of viruses in the computer population, a delay tactics technique was used with the artificial decay parameters like different types of antivirus. The mathematical delayed model is designed with the whole computer population divided into subpopulations: susceptible, antidotal, exposed, infected, quarantined, and recovered. The fundamental properties of the newly developed model were studied rigorously like the positivity and boundedness of the results. Also, the two states discussed the computer population like computer virus–free equilibrium (virus control in computer populations) and computer virus–existing equilibrium (virus active to affect a computer population). Established concepts such as the Routh–Hurwitz criterion and Lyapunov function stabilities for both states of the model at the local and global levels under certain assumptions of reproduction number. The simulation results support the theoretical analysis of the model and the best presentation of results in each computer subpopulation. Also, these results visualize the gaining virus capacity and controlling virus with the effective use of delay tactics including or without antivirus software.

Suggested Citation

  • Ali Raza & Eugénio M. Rocha & Mohammed Mahyoub Al-Shamiri & Nauman Ahmed & Muhammad Rafiq & Maysaa Elmahi Abd Elwahab & Emad Fadhal, 2025. "Transmission Dynamics of Computer Virus Propagation Model Through Delay Effect Demonstration," Journal of Mathematics, John Wiley & Sons, vol. 2025(1).
  • Handle: RePEc:wly:jjmath:v:2025:y:2025:i:1:n:9971453
    DOI: 10.1155/jom/9971453
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    References listed on IDEAS

    as
    1. Ali Raza & Eugenio Rocha & Emad Fadhal & Rashid I. H. Ibrahim & Eman Afkar & Muhammad Bilal & Guilherme Guilherme Ferraz de Arruda, 2024. "The Effect of Delay Techniques on a Lassa Fever Epidemic Model," Complexity, Hindawi, vol. 2024, pages 1-17, June.
    2. Singh, Jagdev & Kumar, Devendra & Hammouch, Zakia & Atangana, Abdon, 2018. "A fractional epidemiological model for computer viruses pertaining to a new fractional derivative," Applied Mathematics and Computation, Elsevier, vol. 316(C), pages 504-515.
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