Recoverable prevalence in growing scale-free networks and the effective immunization
arXiv:cond-mat/0305549 · doi:10.1103/PhysRevE.69.016112
Abstract
We study the persistent recoverable prevalence and the extinction of computer viruses via e-mails on a growing scale-free network with new users, which structure is estimated form real data. The typical phenomenon is simulated in a realistic model with the probabilistic execution and detection of viruses. Moreover, the conditions of extinction by random and targeted immunizations for hubs are derived through bifurcation analysis for simpler models by using a mean-field approximation without the connectivity correlations. We can qualitatively understand the mechanisms of the spread in linearly growing scale-free networks.
9 pages, 9 figures, 1 table. Update version after helpful referee comments
References in corpus (14)
- Statistical mechanics of complex networks
- Error and attack tolerance of complex networks
- The spread of epidemic disease on networks
- Mean-field theory for scale-free random networks
- Epidemic dynamics and endemic states in complex networks
- Dynamical and correlation properties of the Internet
- Topology of evolving networks: local events and universality
- Immunization of complex networks
- Scale-free topology of e-mail networks
- Organization of Growing Random Networks
- Halting viruses in scale-free networks
- Are randomly grown graphs really random?
- Anomalous percolating properties of growing networks
- Mechanisms of recoverable prevalence and extinction of viruses on linearly growing scale-free networks
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