Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2021, Cilt: 50 Sayı: 5, 1384 - 1400, 15.10.2021
https://doi.org/10.15672/hujms.747872

Öz

Kaynakça

  • [1] R. Anguelov and J.M-S. Lubuma, Contributions to the mathematics of the nonstandard finite difference method and applications, Numer. Methods Partial Differential Equations, 17, 518–543, 2001.
  • [2] R. Anguelov and J.M-S. Lubuma, Nonstandard finite difference method by nonlocal approximation, Math. Comput. Simulation, 61 (3-6), 465–475, 2003.
  • [3] R. Anguelov, K. Dukuza and J.M-S. Lubuma, Backward bifurcation analysis for two continuous and discrete epidemiological models, Math. Methods Appl. Sci. 41 (18), 8784– 8798, 2018.
  • [4] R.M. Anderson and R.M. May, Infectious Diseases of Humans: Dynamics and Control, Oxford University Press, USA, 1992.
  • [5] C. Castillo-Chavez and B. Song, Dynamical models of tuberculosis and their applica- tions, Math. Biosci. Engin. 1, 361–404, 2004.
  • [6] L.C. Chen and K.M. Carley, The impact of countermeasure propagation on the preva- lence of computer viruses, IEEE Trans. Syst., Man, Cybern. B. Cybern. 34 (2), 823–833, 2004.
  • [7] CSI/FBI; Computer crime and security survey. www.gocsi.com, 2008. Accessed 26 March 2020.
  • [8] J.D. Crawford, Introduction to bifurcation theory, Rev. Modern Phys. 63 (4), 991, 1991.
  • [9] Q.A. Dang and M.T. Hoang, Positivity and global stability preserving NSFD schemes for a mixing propagation model of computer viruses, J. Comput. Appl. Math. 374, 112753, 2020.
  • [10] D.T. Dimitrov and H.V. Kojouharov, Positive and elementary stable nonstandard numerical methods with applications to predator-prey models, J. Comput. Appl. Math. 189 (1-2), 98–108, 2006.
  • [11] N.K.K. Dukuza, Centre Manifold Theory for some Continuous and Discrete Epidemi- ological Models, University of Pretoria, PhD Thesis, South Africa, 2019.
  • [12] J. Guckenheimer and P. Holmes, Nonlinear oscillations, dynamical systems, and bi- furcations of vector fields, 42, Springer Science & Business Media, 2013.
  • [13] J.M. Heffernan, R.J. Smith and L.M. Wahl, Perspectives on the basic reproductive ratio, J. R. Soc. Interface, 2 (4), 281–293, 2005.
  • [14] P. Kama, Non-standard finite difference methods in dynamical systems, University of Pretoria, PhD Thesis, South Africa, 2009.
  • [15] W.O. Kermack and A.G. McKendrick, A contribution to the mathematical theory of epidemics, The Royal Society London, Proc. R. Soc. Lond. 115 (772), 700–721, 1927.
  • [16] W.O. Kermack and A.G. McKendrick, Contributions to the mathematical theory of epidemics. II.The problem of endemicity. The Royal Society London, Proc. R. Soc. Lond. 138 (834), 55–83, 1932.
  • [17] R. Mickens, Nonstandard Finite Difference Models of Differential Equations, World Scientific, Hackensack, NJ, 1994.
  • [18] B.K. Mishra and D.K. Saini, SEIRS epidemic model with delay for transmission of malicious objects in computer network, Appl. Math. Comput. 188 (2), 1476–1482, 2007.
  • [19] W.H. Murray,The application of epidemiology to computer viruses, Comput. Secur. 7 (2), 130–150, 1988.
  • [20] J.R.C. Piqueira, A.A. de Vasconcelos, C.E.C.J. Gabriel and V.O. Araujo, Dynamic models for computer viruses, Comput. Secur. 27 (7-8), 355–359, 2008.
  • [21] P. Van den Driessche and J. Watmough, Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission, Math. Biosci. 180 (1-2), 29–48, 2002.
  • [22] S. Wiggins, Introduction to Applied Nonlinear Dynamical Systems and Chaos, Springer-Verlag, Berlin, 1990.
  • [23] H. Yuan, G. Chen, J. Wu and H. Xiong, Towards controlling virus propagation in information systems with point-to-group information sharing, Decis. Support Syst. 48 (1), 57–68, 2009.
  • [24] Q. Zhu, X. Yang, L. Yang and X. Zhang, A mixing propagation model of computer viruses and countermeasures, Nonlinear Dynam. 73, 1433–1441, 2013.

Bifurcation analysis of a computer virus propagation model

Yıl 2021, Cilt: 50 Sayı: 5, 1384 - 1400, 15.10.2021
https://doi.org/10.15672/hujms.747872

Öz

We propose a mathematical model for investigating the efficacy of Countermeasure Competing (CMC) strategy which is a method for reducing the effect of computer virus attacks. Using the Centre Manifold Theory, we determine conditions under which a subcritical (backward) bifurcation occurs at Basic Reproduction Number $R_{0}=1$. In order to illustrate the theoretical findings, we construct a new Nonstandard Finite Difference Scheme (NSFD) that preserves the bifurcation property at $R_{0}=1$ among other dynamics of the continuous model. Earlier results given by Chen and Carley [The impact of countermeasure propagation on the prevalence of computer viruses, IEEE Trans. Syst., Man, Cybern. B. Cybern. 2004] show that the CMC strategy is effective when the countermeasure propagation rate is higher than the virus spreading rate. Our results reveal that even if this condition is not met, the CMC strategy may still successfully eradicate computer viruses depending on the extent of its effectiveness. 

Kaynakça

  • [1] R. Anguelov and J.M-S. Lubuma, Contributions to the mathematics of the nonstandard finite difference method and applications, Numer. Methods Partial Differential Equations, 17, 518–543, 2001.
  • [2] R. Anguelov and J.M-S. Lubuma, Nonstandard finite difference method by nonlocal approximation, Math. Comput. Simulation, 61 (3-6), 465–475, 2003.
  • [3] R. Anguelov, K. Dukuza and J.M-S. Lubuma, Backward bifurcation analysis for two continuous and discrete epidemiological models, Math. Methods Appl. Sci. 41 (18), 8784– 8798, 2018.
  • [4] R.M. Anderson and R.M. May, Infectious Diseases of Humans: Dynamics and Control, Oxford University Press, USA, 1992.
  • [5] C. Castillo-Chavez and B. Song, Dynamical models of tuberculosis and their applica- tions, Math. Biosci. Engin. 1, 361–404, 2004.
  • [6] L.C. Chen and K.M. Carley, The impact of countermeasure propagation on the preva- lence of computer viruses, IEEE Trans. Syst., Man, Cybern. B. Cybern. 34 (2), 823–833, 2004.
  • [7] CSI/FBI; Computer crime and security survey. www.gocsi.com, 2008. Accessed 26 March 2020.
  • [8] J.D. Crawford, Introduction to bifurcation theory, Rev. Modern Phys. 63 (4), 991, 1991.
  • [9] Q.A. Dang and M.T. Hoang, Positivity and global stability preserving NSFD schemes for a mixing propagation model of computer viruses, J. Comput. Appl. Math. 374, 112753, 2020.
  • [10] D.T. Dimitrov and H.V. Kojouharov, Positive and elementary stable nonstandard numerical methods with applications to predator-prey models, J. Comput. Appl. Math. 189 (1-2), 98–108, 2006.
  • [11] N.K.K. Dukuza, Centre Manifold Theory for some Continuous and Discrete Epidemi- ological Models, University of Pretoria, PhD Thesis, South Africa, 2019.
  • [12] J. Guckenheimer and P. Holmes, Nonlinear oscillations, dynamical systems, and bi- furcations of vector fields, 42, Springer Science & Business Media, 2013.
  • [13] J.M. Heffernan, R.J. Smith and L.M. Wahl, Perspectives on the basic reproductive ratio, J. R. Soc. Interface, 2 (4), 281–293, 2005.
  • [14] P. Kama, Non-standard finite difference methods in dynamical systems, University of Pretoria, PhD Thesis, South Africa, 2009.
  • [15] W.O. Kermack and A.G. McKendrick, A contribution to the mathematical theory of epidemics, The Royal Society London, Proc. R. Soc. Lond. 115 (772), 700–721, 1927.
  • [16] W.O. Kermack and A.G. McKendrick, Contributions to the mathematical theory of epidemics. II.The problem of endemicity. The Royal Society London, Proc. R. Soc. Lond. 138 (834), 55–83, 1932.
  • [17] R. Mickens, Nonstandard Finite Difference Models of Differential Equations, World Scientific, Hackensack, NJ, 1994.
  • [18] B.K. Mishra and D.K. Saini, SEIRS epidemic model with delay for transmission of malicious objects in computer network, Appl. Math. Comput. 188 (2), 1476–1482, 2007.
  • [19] W.H. Murray,The application of epidemiology to computer viruses, Comput. Secur. 7 (2), 130–150, 1988.
  • [20] J.R.C. Piqueira, A.A. de Vasconcelos, C.E.C.J. Gabriel and V.O. Araujo, Dynamic models for computer viruses, Comput. Secur. 27 (7-8), 355–359, 2008.
  • [21] P. Van den Driessche and J. Watmough, Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission, Math. Biosci. 180 (1-2), 29–48, 2002.
  • [22] S. Wiggins, Introduction to Applied Nonlinear Dynamical Systems and Chaos, Springer-Verlag, Berlin, 1990.
  • [23] H. Yuan, G. Chen, J. Wu and H. Xiong, Towards controlling virus propagation in information systems with point-to-group information sharing, Decis. Support Syst. 48 (1), 57–68, 2009.
  • [24] Q. Zhu, X. Yang, L. Yang and X. Zhang, A mixing propagation model of computer viruses and countermeasures, Nonlinear Dynam. 73, 1433–1441, 2013.
Toplam 24 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Matematik
Bölüm Matematik
Yazarlar

Kenneth Dukuza 0000-0002-4525-7390

Yayımlanma Tarihi 15 Ekim 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 50 Sayı: 5

Kaynak Göster

APA Dukuza, K. (2021). Bifurcation analysis of a computer virus propagation model. Hacettepe Journal of Mathematics and Statistics, 50(5), 1384-1400. https://doi.org/10.15672/hujms.747872
AMA Dukuza K. Bifurcation analysis of a computer virus propagation model. Hacettepe Journal of Mathematics and Statistics. Ekim 2021;50(5):1384-1400. doi:10.15672/hujms.747872
Chicago Dukuza, Kenneth. “Bifurcation Analysis of a Computer Virus Propagation Model”. Hacettepe Journal of Mathematics and Statistics 50, sy. 5 (Ekim 2021): 1384-1400. https://doi.org/10.15672/hujms.747872.
EndNote Dukuza K (01 Ekim 2021) Bifurcation analysis of a computer virus propagation model. Hacettepe Journal of Mathematics and Statistics 50 5 1384–1400.
IEEE K. Dukuza, “Bifurcation analysis of a computer virus propagation model”, Hacettepe Journal of Mathematics and Statistics, c. 50, sy. 5, ss. 1384–1400, 2021, doi: 10.15672/hujms.747872.
ISNAD Dukuza, Kenneth. “Bifurcation Analysis of a Computer Virus Propagation Model”. Hacettepe Journal of Mathematics and Statistics 50/5 (Ekim 2021), 1384-1400. https://doi.org/10.15672/hujms.747872.
JAMA Dukuza K. Bifurcation analysis of a computer virus propagation model. Hacettepe Journal of Mathematics and Statistics. 2021;50:1384–1400.
MLA Dukuza, Kenneth. “Bifurcation Analysis of a Computer Virus Propagation Model”. Hacettepe Journal of Mathematics and Statistics, c. 50, sy. 5, 2021, ss. 1384-00, doi:10.15672/hujms.747872.
Vancouver Dukuza K. Bifurcation analysis of a computer virus propagation model. Hacettepe Journal of Mathematics and Statistics. 2021;50(5):1384-400.