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Novel hybrid mitigation strategy for improving the resiliency of hierarchical networks subjected to attacks

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  • Morehead, Raymond
  • Noore, Afzel

Abstract

This paper studies the resiliency of hierarchical networks when subjected to random errors, static attacks, and cascade attacks. The performance is compared with existing Erdös–Rényi (ER) random networks and Barabasi and Albert (BA) scale-free networks using global efficiency as the common performance metric. The results show that critical infrastructures modeled as hierarchical networks are intrinsically efficient and are resilient to random errors, however they are more vulnerable to targeted attacks than scale-free networks. Based on the response dynamics to different attack models, we propose a novel hybrid mitigation strategy that combines discrete levels of critical node reinforcement with additional edge augmentation. The proposed modified topology takes advantage of the high initial efficiency of the hierarchical network while also making it resilient to attacks. Experimental results show that when the level of damage inflicted on a critical node is low, the node reinforcement strategy is more effective, and as the level of damage increases, the additional edge augmentation is highly effective in maintaining the overall network resiliency.

Suggested Citation

  • Morehead, Raymond & Noore, Afzel, 2007. "Novel hybrid mitigation strategy for improving the resiliency of hierarchical networks subjected to attacks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 378(2), pages 603-612.
  • Handle: RePEc:eee:phsmap:v:378:y:2007:i:2:p:603-612
    DOI: 10.1016/j.physa.2006.12.018
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    References listed on IDEAS

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    1. Barabási, Albert-László & Albert, Réka & Jeong, Hawoong, 2000. "Scale-free characteristics of random networks: the topology of the world-wide web," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 281(1), pages 69-77.
    2. 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.
    3. Réka Albert & Hawoong Jeong & Albert-László Barabási, 2000. "Error and attack tolerance of complex networks," Nature, Nature, vol. 406(6794), pages 378-382, July.
    4. D. S. Callaway & J. E. Hopcroft & J. M. Kleinberg & M. E. J. Newman & S. H. Strogatz, 2001. "Are Randomly Grown Graphs Really Random?," Working Papers 01-05-025, Santa Fe Institute.
    5. 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.
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    Cited by:

    1. Zhu, Qian & Zhu, Zhiliang & Qi, Yi & Yu, Hai & Xu, Yanjie, 2018. "Optimization of cascading failure on complex network based on NNIA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 42-51.

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