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The Impact of the Network Topology on the Viral Prevalence: A Node-Based Approach
This paper addresses the impact of the structure of the viral propagation network on the viral prevalence. For that purpose, a new epidemic model of computer virus, known as the node-based SLBS model, is proposed. Our analysis shows that the maximum eigenvalue of the underlying network is a key fact...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4519130/ https://www.ncbi.nlm.nih.gov/pubmed/26222539 http://dx.doi.org/10.1371/journal.pone.0134507 |
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author | Yang, Lu-Xing Draief, Moez Yang, Xiaofan |
author_facet | Yang, Lu-Xing Draief, Moez Yang, Xiaofan |
author_sort | Yang, Lu-Xing |
collection | PubMed |
description | This paper addresses the impact of the structure of the viral propagation network on the viral prevalence. For that purpose, a new epidemic model of computer virus, known as the node-based SLBS model, is proposed. Our analysis shows that the maximum eigenvalue of the underlying network is a key factor determining the viral prevalence. Specifically, the value range of the maximum eigenvalue is partitioned into three subintervals: viruses tend to extinction very quickly or approach extinction or persist depending on into which subinterval the maximum eigenvalue of the propagation network falls. Consequently, computer virus can be contained by adjusting the propagation network so that its maximum eigenvalue falls into the desired subinterval. |
format | Online Article Text |
id | pubmed-4519130 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-45191302015-07-31 The Impact of the Network Topology on the Viral Prevalence: A Node-Based Approach Yang, Lu-Xing Draief, Moez Yang, Xiaofan PLoS One Research Article This paper addresses the impact of the structure of the viral propagation network on the viral prevalence. For that purpose, a new epidemic model of computer virus, known as the node-based SLBS model, is proposed. Our analysis shows that the maximum eigenvalue of the underlying network is a key factor determining the viral prevalence. Specifically, the value range of the maximum eigenvalue is partitioned into three subintervals: viruses tend to extinction very quickly or approach extinction or persist depending on into which subinterval the maximum eigenvalue of the propagation network falls. Consequently, computer virus can be contained by adjusting the propagation network so that its maximum eigenvalue falls into the desired subinterval. Public Library of Science 2015-07-29 /pmc/articles/PMC4519130/ /pubmed/26222539 http://dx.doi.org/10.1371/journal.pone.0134507 Text en © 2015 Yang 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Yang, Lu-Xing Draief, Moez Yang, Xiaofan The Impact of the Network Topology on the Viral Prevalence: A Node-Based Approach |
title | The Impact of the Network Topology on the Viral Prevalence: A Node-Based Approach |
title_full | The Impact of the Network Topology on the Viral Prevalence: A Node-Based Approach |
title_fullStr | The Impact of the Network Topology on the Viral Prevalence: A Node-Based Approach |
title_full_unstemmed | The Impact of the Network Topology on the Viral Prevalence: A Node-Based Approach |
title_short | The Impact of the Network Topology on the Viral Prevalence: A Node-Based Approach |
title_sort | impact of the network topology on the viral prevalence: a node-based approach |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4519130/ https://www.ncbi.nlm.nih.gov/pubmed/26222539 http://dx.doi.org/10.1371/journal.pone.0134507 |
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