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Vulnerability metrics and analysis for communities in complex networks

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  • Rocco S., Claudio M.
  • Ramirez-Marquez, José Emmanuel

Abstract

This paper applies the problem of community detection in complex networks to identify sets of network elements that are critical to the connectivity of the network and its communities. Specifically, the paper defines a vulnerability set and value for each of the communities in a complex network. Also, for each community it identifies a value of relative vulnerability in comparison with the remaining communities. The approach allows to visualize/identify the critical elements of a complex network. This is an important first step for many recent problems arising in social networks, critical infrastructures and homeland security. By identifying these elements one can prioritize resource allocation to protect, interdict or improve performance in these types of systems. The sets and metrics introduced are illustrated with numerous examples and discussions. Based on the analysis of the examples the manuscript provides an intuitive description of a community's presence in the interior or periphery of a network.

Suggested Citation

  • Rocco S., Claudio M. & Ramirez-Marquez, José Emmanuel, 2011. "Vulnerability metrics and analysis for communities in complex networks," Reliability Engineering and System Safety, Elsevier, vol. 96(10), pages 1360-1366.
    • Handle: RePEc:eee:reensy:v:96:y:2011:i:10:p:1360-1366
    DOI: 10.1016/j.ress.2011.03.001
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    References listed on IDEAS

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    1. E. Zio, 2007. "From complexity science to reliability efficiency: a new way of looking at complex network systems and critical infrastructures," International Journal of Critical Infrastructures, Inderscience Enterprises Ltd, vol. 3(3/4), pages 488-508.
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    Cited by:

    1. Chen, Gaolin & Zhou, Shuming & Li, Min & Zhang, Hong, 2022. "Evaluation of community vulnerability based on communicability and structural dissimilarity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    2. Meng, Xiangkun & Li, Xinhong & Wang, Weigang & Song, Guozheng & Chen, Guoming & Zhu, Jingyu, 2021. "A novel methodology to analyze accident path in deepwater drilling operation considering uncertain information," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    3. Lu, Lu & Xu, Zhengguo & Wang, Wenhai & Sun, Youxian, 2013. "A new fault detection method for computer networks," Reliability Engineering and System Safety, Elsevier, vol. 114(C), pages 45-51.
    4. Wen, Tao & Gao, Qiuya & Chen, Yu-wang & Cheong, Kang Hao, 2022. "Exploring the vulnerability of transportation networks by entropy: A case study of Asia–Europe maritime transportation network," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    5. Ramirez-Marquez, J.E. & Rocco, C.M. & Moronta, J. & Gama Dessavre, D., 2016. "Robustness in network community detection under links weights uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 88-95.
    6. Li, Y.F. & Sansavini, G. & Zio, E., 2013. "Non-dominated sorting binary differential evolution for the multi-objective optimization of cascading failures protection in complex networks," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 195-205.
    7. Claudio M Rocco & Kash Barker & Jose Moronta & Jose E Ramirez-Marquez, 2018. "Community detection and resilience in multi-source, multi-terminal networks," Journal of Risk and Reliability, , vol. 232(6), pages 616-626, December.
    8. Dui, Hongyan & Meng, Xueyu & Xiao, Hui & Guo, Jianjun, 2020. "Analysis of the cascading failure for scale-free networks based on a multi-strategy evolutionary game," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    9. Alondra Chamorro & Tomás Echaveguren & Eduardo Allen & Marta Contreras & Joaquín Dagá & Hernan de Solminihac & Luis E. Lara, 2020. "Sustainable Risk Management of Rural Road Networks Exposed to Natural Hazards: Application to Volcanic Lahars in Chile," Sustainability, MDPI, vol. 12(17), pages 1-23, August.
    10. Fang, Yi-Ping & Zio, Enrico, 2013. "Unsupervised spectral clustering for hierarchical modelling and criticality analysis of complex networks," Reliability Engineering and System Safety, Elsevier, vol. 116(C), pages 64-74.
    11. Ramirez-Marquez, Jose E. & Rocco, Claudio M. & Barker, Kash & Moronta, Jose, 2018. "Quantifying the resilience of community structures in networks," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 466-474.
    12. Wen, Tao & Deng, Yong, 2020. "The vulnerability of communities in complex networks: An entropy approach," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    13. 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.
    14. Claudio M. Rocco & Kash Barker & Jose Moronta, 2022. "Determining the best algorithm to detect community structures in networks: application to power systems," Environment Systems and Decisions, Springer, vol. 42(2), pages 251-264, June.
    15. Zio, Enrico & Piccinelli, Roberta & Delfanti, Maurizio & Olivieri, Valeria & Pozzi, Mauro, 2012. "Application of the load flow and random flow models for the analysis of power transmission networks," Reliability Engineering and System Safety, Elsevier, vol. 103(C), pages 102-109.
    16. Rocco, Claudio M. & Moronta, José & Ramirez-Marquez, José E. & Barker, Kash, 2017. "Effects of multi-state links in network community detection," Reliability Engineering and System Safety, Elsevier, vol. 163(C), pages 46-56.
    17. Wei, Daijun & Zhang, Xiaoge & Mahadevan, Sankaran, 2018. "Measuring the vulnerability of community structure in complex networks," Reliability Engineering and System Safety, Elsevier, vol. 174(C), pages 41-52.

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