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Rethinking failure and attack tolerance assessment in complex networks

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  • Ghedini, Cinara G.
  • Ribeiro, Carlos H.C.

Abstract

Studies have revealed that real complex networks are inherently vulnerable to the loss of high centrality nodes. These nodes are crucial to maintaining the network connectivity and are identified by classical measures, such as degree and betweenness centralities. Despite its significance, an assessment based solely on this vulnerability premise is misleading for the interpretation of the real state of the network concerning connectivity. As a matter of fact, some networks may be in a state of imminent fragmentation before such a condition is fully characterized by an analysis targeted solely on the centrally positioned nodes. This work aims at showing that, in fact, it is basically the global network configuration that is responsible for network fragmentation, as it may allow many other lower centrality nodes to seriously damage the network connectivity.

Suggested Citation

  • Ghedini, Cinara G. & Ribeiro, Carlos H.C., 2011. "Rethinking failure and attack tolerance assessment in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4684-4691.
    • Handle: RePEc:eee:phsmap:v:390:y:2011:i:23:p:4684-4691
    DOI: 10.1016/j.physa.2011.07.006
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    References listed on IDEAS

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    1. Crucitti, Paolo & Latora, Vito & Marchiori, Massimo & Rapisarda, Andrea, 2004. "Error and attack tolerance of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 340(1), pages 388-394.
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    Cited by:

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    2. Chen, Jinqu & Liu, Jie & Peng, Qiyuan & Yin, Yong, 2022. "Resilience assessment of an urban rail transit network: A case study of Chengdu subway," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    3. Ding, Yueting & Zhang, Ming & Chen, Sai & Nie, Rui, 2020. "Assessing the resilience of China’s natural gas importation under network disruptions," Energy, Elsevier, vol. 211(C).
    4. Yingying Xing & Jian Lu & Shengdi Chen & Sunanda Dissanayake, 2017. "Vulnerability analysis of urban rail transit based on complex network theory: a case study of Shanghai Metro," Public Transport, Springer, vol. 9(3), pages 501-525, October.
    5. Ma, A. & Mondragón, R.J., 2012. "Evaluation of network robustness using a node tearing algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(24), pages 6674-6681.
    6. Kashin Sugishita & Yasuo Asakura, 2021. "Vulnerability studies in the fields of transportation and complex networks: a citation network analysis," Public Transport, Springer, vol. 13(1), pages 1-34, March.
    7. Chen, Sai & Ding, Yueting & Zhang, Yanfang & Zhang, Ming & Nie, Rui, 2022. "Study on the robustness of China's oil import network," Energy, Elsevier, vol. 239(PB).
    8. Saniee Monfared, Momhammad Ali & Jalili, Mahdi & Alipour, Zohreh, 2014. "Topology and vulnerability of the Iranian power grid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 24-33.
    9. Peng, Xingzhao & Yao, Hong & Du, Jun & Wang, Zhe & Ding, Chao, 2015. "Invulnerability of scale-free network against critical node failures based on a renewed cascading failure model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 69-77.
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    11. Viljoen, Nadia M. & Joubert, Johan W., 2016. "The vulnerability of the global container shipping network to targeted link disruption," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 396-409.
    12. Milena Oehlers & Benjamin Fabian, 2021. "Graph Metrics for Network Robustness—A Survey," Mathematics, MDPI, vol. 9(8), pages 1-48, April.

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