Fast fragmentation of networks using module-based attacks
Autor(a) principal: | |
---|---|
Data de Publicação: | 2015 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/131380 |
Resumo: | In the multidisciplinary field of Network Science, optimization of procedures for efficiently breaking complex networks is attracting much attention from a practical point of view. In this contribution, we present a module-based method to efficiently fragment complex networks. The procedure firstly identifies topological communities through which the network can be represented using a well established heuristic algorithm of community finding. Then only the nodes that participate of inter-community links are removed in descending order of their betweenness centrality. We illustrate the method by applying it to a variety of examples in the social, infrastructure, and biological fields. It is shown that the module-based approach always outperforms targeted attacks to vertices based on node degree or betweenness centrality rankings, with gains in efficiency strongly related to the modularity of the network. Remarkably, in the US power grid case, by deleting 3% of the nodes, the proposed method breaks the original network in fragments which are twenty times smaller in size than the fragments left by betweenness-based attack. |
id |
UFRGS-2_6d11bef6f248362d1e12a805b0a9cabc |
---|---|
oai_identifier_str |
oai:www.lume.ufrgs.br:10183/131380 |
network_acronym_str |
UFRGS-2 |
network_name_str |
Repositório Institucional da UFRGS |
repository_id_str |
|
spelling |
Cunha, Bruno Requião daGonzález-Avella, Juan CarlosGoncalves, Sebastian2015-12-25T02:39:13Z20151932-6203http://hdl.handle.net/10183/131380000980436In the multidisciplinary field of Network Science, optimization of procedures for efficiently breaking complex networks is attracting much attention from a practical point of view. In this contribution, we present a module-based method to efficiently fragment complex networks. The procedure firstly identifies topological communities through which the network can be represented using a well established heuristic algorithm of community finding. Then only the nodes that participate of inter-community links are removed in descending order of their betweenness centrality. We illustrate the method by applying it to a variety of examples in the social, infrastructure, and biological fields. It is shown that the module-based approach always outperforms targeted attacks to vertices based on node degree or betweenness centrality rankings, with gains in efficiency strongly related to the modularity of the network. Remarkably, in the US power grid case, by deleting 3% of the nodes, the proposed method breaks the original network in fragments which are twenty times smaller in size than the fragments left by betweenness-based attack.application/pdfengPLoS ONE. San Francisco. Vol. 10, no. 11 (Nov. 2015), e0142824, 15 p.Teoria de redesSimulação computacionalFast fragmentation of networks using module-based attacksEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSORIGINAL000980436.pdf000980436.pdfTexto completo (inglês)application/pdf2773760http://www.lume.ufrgs.br/bitstream/10183/131380/1/000980436.pdf53381eeeb72ab043e4e4c7465fa3d30dMD51TEXT000980436.pdf.txt000980436.pdf.txtExtracted Texttext/plain46796http://www.lume.ufrgs.br/bitstream/10183/131380/2/000980436.pdf.txt439fc9a9335e124a954a35c94f451378MD52THUMBNAIL000980436.pdf.jpg000980436.pdf.jpgGenerated Thumbnailimage/jpeg1933http://www.lume.ufrgs.br/bitstream/10183/131380/3/000980436.pdf.jpgdb8de990625b32bb83e68836a145d1ffMD5310183/1313802024-05-19 05:46:11.368936oai:www.lume.ufrgs.br:10183/131380Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2024-05-19T08:46:11Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
Fast fragmentation of networks using module-based attacks |
title |
Fast fragmentation of networks using module-based attacks |
spellingShingle |
Fast fragmentation of networks using module-based attacks Cunha, Bruno Requião da Teoria de redes Simulação computacional |
title_short |
Fast fragmentation of networks using module-based attacks |
title_full |
Fast fragmentation of networks using module-based attacks |
title_fullStr |
Fast fragmentation of networks using module-based attacks |
title_full_unstemmed |
Fast fragmentation of networks using module-based attacks |
title_sort |
Fast fragmentation of networks using module-based attacks |
author |
Cunha, Bruno Requião da |
author_facet |
Cunha, Bruno Requião da González-Avella, Juan Carlos Goncalves, Sebastian |
author_role |
author |
author2 |
González-Avella, Juan Carlos Goncalves, Sebastian |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Cunha, Bruno Requião da González-Avella, Juan Carlos Goncalves, Sebastian |
dc.subject.por.fl_str_mv |
Teoria de redes Simulação computacional |
topic |
Teoria de redes Simulação computacional |
description |
In the multidisciplinary field of Network Science, optimization of procedures for efficiently breaking complex networks is attracting much attention from a practical point of view. In this contribution, we present a module-based method to efficiently fragment complex networks. The procedure firstly identifies topological communities through which the network can be represented using a well established heuristic algorithm of community finding. Then only the nodes that participate of inter-community links are removed in descending order of their betweenness centrality. We illustrate the method by applying it to a variety of examples in the social, infrastructure, and biological fields. It is shown that the module-based approach always outperforms targeted attacks to vertices based on node degree or betweenness centrality rankings, with gains in efficiency strongly related to the modularity of the network. Remarkably, in the US power grid case, by deleting 3% of the nodes, the proposed method breaks the original network in fragments which are twenty times smaller in size than the fragments left by betweenness-based attack. |
publishDate |
2015 |
dc.date.accessioned.fl_str_mv |
2015-12-25T02:39:13Z |
dc.date.issued.fl_str_mv |
2015 |
dc.type.driver.fl_str_mv |
Estrangeiro info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10183/131380 |
dc.identifier.issn.pt_BR.fl_str_mv |
1932-6203 |
dc.identifier.nrb.pt_BR.fl_str_mv |
000980436 |
identifier_str_mv |
1932-6203 000980436 |
url |
http://hdl.handle.net/10183/131380 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
PLoS ONE. San Francisco. Vol. 10, no. 11 (Nov. 2015), e0142824, 15 p. |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFRGS instname:Universidade Federal do Rio Grande do Sul (UFRGS) instacron:UFRGS |
instname_str |
Universidade Federal do Rio Grande do Sul (UFRGS) |
instacron_str |
UFRGS |
institution |
UFRGS |
reponame_str |
Repositório Institucional da UFRGS |
collection |
Repositório Institucional da UFRGS |
bitstream.url.fl_str_mv |
http://www.lume.ufrgs.br/bitstream/10183/131380/1/000980436.pdf http://www.lume.ufrgs.br/bitstream/10183/131380/2/000980436.pdf.txt http://www.lume.ufrgs.br/bitstream/10183/131380/3/000980436.pdf.jpg |
bitstream.checksum.fl_str_mv |
53381eeeb72ab043e4e4c7465fa3d30d 439fc9a9335e124a954a35c94f451378 db8de990625b32bb83e68836a145d1ff |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 |
repository.name.fl_str_mv |
Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS) |
repository.mail.fl_str_mv |
|
_version_ |
1801224893254074368 |