Robustness of correlated networks against propagating attacks

Physics – Physics and Society

Scientific paper

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6 pages, 13 figures

Scientific paper

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. This behavior is related to the layered network structure inevitably generated by a rewiring procedure we adopt to realize correlated networks.

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