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Topological Vulnerability Evaluation Model Based on Fractal Dimension of Complex Networks

With an increasing emphasis on network security, much more attentions have been attracted to the vulnerability of complex networks. In this paper, the fractal dimension, which can reflect space-filling capacity of networks, is redefined as the origin moment of the edge betweenness to obtain a more r...

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Detalles Bibliográficos
Autores principales: Gou, Li, Wei, Bo, Sadiq, Rehan, Sadiq, Yong, Deng, Yong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4709056/
https://www.ncbi.nlm.nih.gov/pubmed/26751371
http://dx.doi.org/10.1371/journal.pone.0146896
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author Gou, Li
Wei, Bo
Sadiq, Rehan
Sadiq, Yong
Deng, Yong
author_facet Gou, Li
Wei, Bo
Sadiq, Rehan
Sadiq, Yong
Deng, Yong
author_sort Gou, Li
collection PubMed
description With an increasing emphasis on network security, much more attentions have been attracted to the vulnerability of complex networks. In this paper, the fractal dimension, which can reflect space-filling capacity of networks, is redefined as the origin moment of the edge betweenness to obtain a more reasonable evaluation of vulnerability. The proposed model combining multiple evaluation indexes not only overcomes the shortage of average edge betweenness’s failing to evaluate vulnerability of some special networks, but also characterizes the topological structure and highlights the space-filling capacity of networks. The applications to six US airline networks illustrate the practicality and effectiveness of our proposed method, and the comparisons with three other commonly used methods further validate the superiority of our proposed method.
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spelling pubmed-47090562016-01-15 Topological Vulnerability Evaluation Model Based on Fractal Dimension of Complex Networks Gou, Li Wei, Bo Sadiq, Rehan Sadiq, Yong Deng, Yong PLoS One Research Article With an increasing emphasis on network security, much more attentions have been attracted to the vulnerability of complex networks. In this paper, the fractal dimension, which can reflect space-filling capacity of networks, is redefined as the origin moment of the edge betweenness to obtain a more reasonable evaluation of vulnerability. The proposed model combining multiple evaluation indexes not only overcomes the shortage of average edge betweenness’s failing to evaluate vulnerability of some special networks, but also characterizes the topological structure and highlights the space-filling capacity of networks. The applications to six US airline networks illustrate the practicality and effectiveness of our proposed method, and the comparisons with three other commonly used methods further validate the superiority of our proposed method. Public Library of Science 2016-01-11 /pmc/articles/PMC4709056/ /pubmed/26751371 http://dx.doi.org/10.1371/journal.pone.0146896 Text en © 2016 Gou et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Gou, Li
Wei, Bo
Sadiq, Rehan
Sadiq, Yong
Deng, Yong
Topological Vulnerability Evaluation Model Based on Fractal Dimension of Complex Networks
title Topological Vulnerability Evaluation Model Based on Fractal Dimension of Complex Networks
title_full Topological Vulnerability Evaluation Model Based on Fractal Dimension of Complex Networks
title_fullStr Topological Vulnerability Evaluation Model Based on Fractal Dimension of Complex Networks
title_full_unstemmed Topological Vulnerability Evaluation Model Based on Fractal Dimension of Complex Networks
title_short Topological Vulnerability Evaluation Model Based on Fractal Dimension of Complex Networks
title_sort topological vulnerability evaluation model based on fractal dimension of complex networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4709056/
https://www.ncbi.nlm.nih.gov/pubmed/26751371
http://dx.doi.org/10.1371/journal.pone.0146896
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