Robustness of correlated networks against propagating attacks
arXiv:1203.3621 · doi:10.1140/epjb/e2012-30290-0
Abstract
We investigate robustness of correlated networks against propagating attacks modeled by a susceptible-infected-removed model. By Monte-Carlo simulations, we numerically determine the first critical infection rate, above which a global outbreak of disease occurs, and the second critical infection rate, above which disease disintegrates the network. Our result shows that correlated networks are robust compared to the uncorrelated ones, regardless of whether they are assortative or disassortative, when a fraction of infected nodes in an initial state is not too large. For large initial fraction, disassortative network becomes fragile while assortative network holds robustness. This behavior is related to the layered network structure inevitably generated by a rewiring procedure we adopt to realize correlated networks.
6 pages, 13 figures
References in corpus (26)
- Statistical mechanics of complex networks
- The structure and function of complex networks
- Error and attack tolerance of complex networks
- Epidemic spreading in scale-free networks
- Assortative mixing in networks
- Mixing patterns in networks
- Network robustness and fragility: Percolation on random graphs
- Resilience of the Internet to random breakdowns
- Critical phenomena in complex networks
- Attack vulnerability of complex networks
- Breakdown of the Internet under intentional attack
- Absence of epidemic threshold in scale-free networks with connectivity correlations
- Stability and topology of scale-free networks under attack and defense strategies
- Threshold effects for two pathogens spreading on a network
- Resilience to damage of graphs with degree correlations
- Construction and properties of assortative random networks
- Percolation on correlated networks
- Robustness of onion-like correlated networks against targeted attacks
- Immunization of networks with community structure
- Size of Outbreaks Near the Epidemic Threshold
- Cavity analysis on the robustness of random networks against targeted attacks: Influences of degree-degree correlations
- Monte-Carlo simulation study of the two-stage percolation transition in enhanced binary trees
- Solution of an infection model near threshold
- Effect of degree correlations above the first shell on the percolation transition
- Decelerated spreading in degree-correlated networks
- Robustness of networks against propagating attacks under vaccination strategies