2015
DOI: 10.1371/journal.pone.0134507
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Abstract: This paper addresses the impact of the structure of the viral propagation network on the viral prevalence. For that purpose, a new epidemic model of computer virus, known as the node-based SLBS model, is proposed. Our analysis shows that the maximum eigenvalue of the underlying network is a key factor determining the viral prevalence. Specifically, the value range of the maximum eigenvalue is partitioned into three subintervals: viruses tend to extinction very quickly or approach extinction or persist dependin… Show more

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Cited by 63 publications
(29 citation statements)
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References 40 publications
(34 reference statements)
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“…Second, some optimal control strategies [21,22] may be considered. Finally, the next work is to study the impact of the network topology on virus diffusion [23,24].…”
Section: Resultsmentioning
confidence: 99%
“…Second, some optimal control strategies [21,22] may be considered. Finally, the next work is to study the impact of the network topology on virus diffusion [23,24].…”
Section: Resultsmentioning
confidence: 99%
“…Second, delays [43][44][45], pulses [46,47], and random fluctuations [15] may be incorporated to controlled node-level models. Last, but not least, it is worthy to carry out research on the impact of the network topology [9,25,48,49] on the dynamic countermeasure strategy.…”
Section: Discussionmentioning
confidence: 99%
“…In order to study the long-term behavior of computer virus and suppress viral spread macroscopically, a large number of dynamical models have been proposed in the past few decades (for the related references, see, e.g., [1][2][3][4][5][6][7][8][9][10][11]). From the perspective of the division scale of computers on networks, these models can be roughly divided into two categories: compartment-level models and node-level models.…”
Section: Introductionmentioning
confidence: 99%
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“…Yang and X. Yang proposed an epidemic model of computer viruses over a reduced scale-free network [6]. Yang and his partners proposed a node-based susceptiblelatent-breaking-susceptible (SLBS) model which addresses the impact of the structure of the viral propagation network on the viral prevalence [7]. To understand the impact of available information in the control of malicious network epidemics, Mishra and three others proposed a 1---1 type differential epidemic model, where the differentiability allows 2 Discrete Dynamics in Nature and Society a symptom based classification [8].…”
Section: Introductionmentioning
confidence: 99%