Robustness of correlated networks against propagating attacks

  • T. Hasegawa
  • K. Konno
  • K. Nemoto
Regular Article

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.

Keywords

Statistical and Nonlinear Physics 

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Copyright information

© EDP Sciences, SIF, Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • T. Hasegawa
    • 1
  • K. Konno
    • 2
  • K. Nemoto
    • 2
  1. 1.Graduate School of Information SciencesTohoku UniversitySendaiJapan
  2. 2.Department of PhysicsGraduate School of ScienceSapporoJapan

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