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
AUTHORS (3)
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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