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Evaluating the damage associated with intentional network disintegration

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  • Levitin, G.
  • Gertsbakh, I.
  • Shpungin, Y.

Abstract

This paper presents a method for evaluating an expected damage associated with disintegrating complex networks with a given topology into isolated sub-networks (clusters) as a result of intentional attack on randomly chosen network links. The method is based on a multi-dimensional spectra approach for evaluating the probability of network disintegration into a given number of sub-networks when a fixed number of randomly chosen links is eliminated. It also uses the contest success function that evaluates destruction probability of individual links as a function of per-link attack and defense efforts. It is assumed that the defender has no information about the attacker's actions and the attacker has no information about the network structure. The method allows the analysts to compare different network topologies and to choose one with the minimal expected damage under conditions of uncertainty. Illustrative examples are presented.

Suggested Citation

  • Levitin, G. & Gertsbakh, I. & Shpungin, Y., 2011. "Evaluating the damage associated with intentional network disintegration," Reliability Engineering and System Safety, Elsevier, vol. 96(4), pages 433-439.
    • Handle: RePEc:eee:reensy:v:96:y:2011:i:4:p:433-439
    DOI: 10.1016/j.ress.2010.12.022
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    11. Ramirez-Marquez, Jose E. & Rocco S, Claudio M. & Levitin, Gregory, 2009. "Optimal protection of general source–sink networks via evolutionary techniques," Reliability Engineering and System Safety, Elsevier, vol. 94(10), pages 1676-1684.
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    Cited by:

    1. Argenti, Francesca & Landucci, Gabriele & Reniers, Genserik & Cozzani, Valerio, 2018. "Vulnerability assessment of chemical facilities to intentional attacks based on Bayesian Network," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 515-530.
    2. Wei Wang & Francesco Di Maio & Enrico Zio, 2019. "Adversarial Risk Analysis to Allocate Optimal Defense Resources for Protecting Cyber–Physical Systems from Cyber Attacks," Risk Analysis, John Wiley & Sons, vol. 39(12), pages 2766-2785, December.
    3. Levitin, G. & Gertsbakh, I. & Shpungin, Y., 2013. "Evaluating the damage associated with intentional supply deprivation in multi-commodity network," Reliability Engineering and System Safety, Elsevier, vol. 119(C), pages 11-17.
    4. He Yi & Narayanaswamy Balakrishnan & Lirong Cui, 2021. "Comparisons of Multi-State Systems with Binary Components of Different Sizes," Methodology and Computing in Applied Probability, Springer, vol. 23(4), pages 1309-1321, December.
    5. Zarezadeh, S. & Asadi, M. & Balakrishnan, N., 2014. "Dynamic network reliability modeling under nonhomogeneous Poisson processes," European Journal of Operational Research, Elsevier, vol. 232(3), pages 561-571.
    6. Yi, He & Cui, Lirong & Balakrishnan, Narayanaswamy, 2021. "Computation of survival signatures for multi-state consecutive-k systems," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    7. Serkan Eryilmaz & Altan Tuncel, 2016. "Generalizing the survival signature to unrepairable homogeneous multi‐state systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 63(8), pages 593-599, December.
    8. He Yi & Narayanaswamy Balakrishnan & Lirong Cui, 2022. "On Dependent Multi-State Semi-Coherent Systems Based on Multi-State Joint Signature," Methodology and Computing in Applied Probability, Springer, vol. 24(3), pages 1717-1734, September.

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