2012
DOI: 10.1016/j.mcm.2011.12.010
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Hopf bifurcation analysis of a delayed viral infection model in computer networks

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Cited by 83 publications
(47 citation statements)
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“…Based on the discussion about the distribution of the root of (19) in [25,26], we obtain the expression of cos , say…”
Section: Stability Of the Viral Equilibrium And Existence Of Hopf Bifmentioning
confidence: 99%
See 1 more Smart Citation
“…Based on the discussion about the distribution of the root of (19) in [25,26], we obtain the expression of cos , say…”
Section: Stability Of the Viral Equilibrium And Existence Of Hopf Bifmentioning
confidence: 99%
“…For example, Feng et al [19] studied the Hopf bifurcation of a delayed SIRS viral infection model in computer networks by taking the time delay due to the latent and temporary immune period as the bifurcation parameter. Dong et al [9] proposed a delayed SEIR computer virus model with multistate antivirus and studied the Hopf bifurcation of the model by choosing the delay where the infectious nodes use antivirus software to clean the viruses as the bifurcation parameter.…”
Section: Introductionmentioning
confidence: 99%
“…To this end, many dynamical models describing propagation of computer viruses have been established by scholars at home and abroad. Particularly the classic epidemic models, such as SIRS [3][4][5] model, SEIRS model [6], and SEIQRS model [7,8], are used to investigate the spreading law of computer viruses due to the common feature between the computer virus and the biological virus. Some computer virus models with infectivity in both seizing and latent computers have been also proposed by Yang et al [9][10][11][12][13].…”
Section: Introductionmentioning
confidence: 99%
“…In response to this call, Kephart and White [4,5] explored a few earliest malware epidemic models. Toward this direction, a variety of novel computer infection propagation models, ranging from conventional models such as the SIRS models [6], the SEIRS models [7], and the SICS models [8] to unconventional models such as the delayed models [9,10], the stochastic models [11], and the network-based models [12][13][14], have been frequently reported in the literature.…”
Section: Introductionmentioning
confidence: 99%