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Network vulnerability assessment via bi-objective optimization with a fragmentation approach as proxy

Author

Listed:
  • César Yajure
  • Darihelen Montilla
  • Jose Emmanuel Ramirez-Marquez
  • Claudio M Rocco S

Abstract

The fragmentation of a network is used to understand the effects of element removals on its cohesion. Minimum information is required to fragment a network, namely: the topology of the network. Continuous fragmentation of a network can be used to uncover important/critical elements in the network. This article proposes a bi-objective optimization model that, when solved, provides the most economical network fragmentation strategies for increasing element fragmentation cost. After description and solution of the model, the manuscript describes, via experimentation, how the results of the model can be used as a surrogate metric for understanding element importance performance in real service networks. The experimentation is complemented with a classical example of social network analysis. The results show that the proposed fragmentation models can be used as a guide to identify sets of elements that contribute to the successful performance of a system.

Suggested Citation

  • César Yajure & Darihelen Montilla & Jose Emmanuel Ramirez-Marquez & Claudio M Rocco S, 2013. "Network vulnerability assessment via bi-objective optimization with a fragmentation approach as proxy," Journal of Risk and Reliability, , vol. 227(6), pages 576-585, December.
    • Handle: RePEc:sae:risrel:v:227:y:2013:i:6:p:576-585
    DOI: 10.1177/1748006X13489490
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    References listed on IDEAS

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    1. Zio, E. & Golea, L.R. & Rocco S., C.M., 2012. "Identifying groups of critical edges in a realistic electrical network by multi-objective genetic algorithms," Reliability Engineering and System Safety, Elsevier, vol. 99(C), pages 172-177.
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    3. Crucitti, Paolo & Latora, Vito & Marchiori, Massimo & Rapisarda, Andrea, 2003. "Efficiency of scale-free networks: error and attack tolerance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 320(C), pages 622-642.
    4. Stephen P. Borgatti, 2006. "Identifying sets of key players in a social network," Computational and Mathematical Organization Theory, Springer, vol. 12(1), pages 21-34, April.
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