Publication | Open Access
Thresholds for virus spread on networks
132
Citations
23
References
2008
Year
Network Theory (Electrical Engineering)EngineeringVirus SpreadNetwork AnalysisNetwork RobustnessNetwork DynamicLogical TopologyRandom GraphNetwork InterdictionSocial Network AnalysisNetwork Theory (Organizational Economics)Network EstimationNetworked Computer SystemsVirologyComputer ScienceProbability TheoryNetwork Scale-up MethodInfectious Disease ModelingNetwork ScienceGraph TheoryNetwork BiologyBusinessSpectral Radius
We study how the spread of computer viruses, worms and other self-replicating malware is affected by the logical topology of the network over which they propagate. We consider a model in which each host can be in one of 3 possible states—susceptible, infected or removed (cured and no longer susceptible to infection). We characterize how the size of the population that eventually becomes infected depends on the network topology. Specifically, we show that if the ratio of cure to infection rates is larger than the spectral radius of the graph, and the initial infected population is small, then the final infected population is also small in a sense that can be made precise. Conversely, if this ratio is smaller than the spectral radius, then we show in some graph models of practical interest (including power law random graphs) that the average size of the final infected population is large. These results yield insights into what the critical parameters are in determining virus spread in networks.
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