Robustness of correlated networks against propagating attacks

T. Hasegawa, K. Konno, K. Nemoto

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

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.

Original languageEnglish
Article number262
JournalEuropean Physical Journal B
Volume85
Issue number8
DOIs
Publication statusPublished - 2012 Aug

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics

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