1st International ICST Conference on Performance Evaluation Methodologies and Tools

Research Article

Thresholds for virus spread on networks

  • @INPROCEEDINGS{10.1145/1190095.1190160,
        author={Moez  Draief and Ayalvadi  Ganesh and Laurent  Massoulie},
        title={Thresholds for virus spread on networks},
        proceedings={1st International ICST Conference on Performance Evaluation Methodologies and Tools},
        keywords={SIR epidemic spectral radius random graphs largest connected component},
  • Moez Draief
    Ayalvadi Ganesh
    Laurent Massoulie
    Year: 2012
    Thresholds for virus spread on networks
    DOI: 10.1145/1190095.1190160
Moez Draief1,*, Ayalvadi Ganesh2,*, Laurent Massoulie2,*
  • 1: Centre for Mathematical Sciences, Cambridge CB3 0WB, United Kingdom
  • 2: Microsoft Research, 7 J.J. Thomson Avenue, Cambridge CB3 0FB, United Kingdom
*Contact email: M.Draief@statslab.cam.ac.uk, ajg@microsoft.com, lmassoul@microsoft.com


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.A category with the (minimum) three required fields