Thresholds for virus spread on networks

spectral radius 05C80 68R99 Probability (math.PR) Reed–Frost epidemic 02 engineering and technology 01 natural sciences 90B15 004 510 3. Good health giant component 60K35 0103 physical sciences epidemic threshold FOS: Mathematics 0202 electrical engineering, electronic engineering, information engineering 60J85 05C80;90B15;68R99 random graphs Mathematics - Probability
DOI: 10.1214/07-aap470 Publication Date: 2008-03-25T17:42:04Z
ABSTRACT
19 pages<br/>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 characterise 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 final infected population is large. These results yield insights into what the critical parameters are in determining virus spread in networks.<br/>
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