An analysis of the ways to reduce the vulnerability of networks based on the sequential removal of key elements
The research focuses on the metrics that allow assessing the stability of a graph and centrality measures. Their calculation underlies the percolation of the key elements of the graph. The experiment involved methods for calculating the average path length of vertex connectivity, clustering coeffici...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Saint Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO University)
2021-04-01
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| Series: | Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki |
| Subjects: | |
| Online Access: | https://ntv.ifmo.ru/file/article/20338.pdf |
| _version_ | 1818724614825574400 |
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| author | Kirill V. Semenov Fedor L. Shuvaev Kirill I. Vitenzon |
| author_facet | Kirill V. Semenov Fedor L. Shuvaev Kirill I. Vitenzon |
| author_sort | Kirill V. Semenov |
| collection | DOAJ |
| description | The research focuses on the metrics that allow assessing the stability of a graph and centrality measures. Their calculation underlies the percolation of the key elements of the graph. The experiment involved methods for calculating the average path length of vertex connectivity, clustering coefficient, and graph efficiency based on graph theory. To determine the optimal network stability metric, the principal component method was used, based on the theoretical provisions of mathematical statistics. In this study, the authors solved two scientific tasks: the main and auxiliary ones. The latter was to review the existing network stability metrics, which allowed them to choose the optimal one. The choice of the
metrics was carried out using the principal component method. As a result, the average path length proved to be optimal. The solution of the auxiliary problem enabled the authors to analyze the ways to reduce the network stability based on the sequential removal of key elements, which is the main scientific task of the study. The analysis revealed that the
nodes whose importance is expressed based on the measurement of centrality by degree are best suited for reducing the network stability. To estimate the stability of networks, an original complex two-criterion coefficient was developed. The analysis of the ways to reduce the stability was carried out by measuring this coefficient in model and real networks.
Thus, testing of the proposed methods confirmed their efficiency and enabled their application in various fields of science and technology, e.g., sociology, medicine, physics and radio engineering. |
| first_indexed | 2024-12-17T21:29:13Z |
| format | Article |
| id | doaj.art-3d41ebe804fe463d8d77d23a3bb65ada |
| institution | Directory Open Access Journal |
| issn | 2226-1494 2500-0373 |
| language | English |
| last_indexed | 2024-12-17T21:29:13Z |
| publishDate | 2021-04-01 |
| publisher | Saint Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO University) |
| record_format | Article |
| series | Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki |
| spelling | doaj.art-3d41ebe804fe463d8d77d23a3bb65ada2022-12-21T21:31:57ZengSaint Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO University)Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki2226-14942500-03732021-04-0121224124810.17586/2226-1494-2021-21-2-241-248An analysis of the ways to reduce the vulnerability of networks based on the sequential removal of key elementsKirill V. Semenov0https://orcid.org/0000-0002-0397-4009Fedor L. Shuvaev1https://orcid.org/0000-0001-7502-9455Kirill I. Vitenzon2https://orcid.org/0000-0001-5315-7843D.Sc., Head of Chair, Mozhayskiy Military Space Academy, Saint Petersburg, 197198, Russian FederationPhD, Scientific Researcher, Mozhayskiy Military Space Academy, Saint Petersburg, 197198, Russian FederationPhD Student, Mozhayskiy Military Space Academy, Saint Petersburg, 197198, Russian FederationThe research focuses on the metrics that allow assessing the stability of a graph and centrality measures. Their calculation underlies the percolation of the key elements of the graph. The experiment involved methods for calculating the average path length of vertex connectivity, clustering coefficient, and graph efficiency based on graph theory. To determine the optimal network stability metric, the principal component method was used, based on the theoretical provisions of mathematical statistics. In this study, the authors solved two scientific tasks: the main and auxiliary ones. The latter was to review the existing network stability metrics, which allowed them to choose the optimal one. The choice of the metrics was carried out using the principal component method. As a result, the average path length proved to be optimal. The solution of the auxiliary problem enabled the authors to analyze the ways to reduce the network stability based on the sequential removal of key elements, which is the main scientific task of the study. The analysis revealed that the nodes whose importance is expressed based on the measurement of centrality by degree are best suited for reducing the network stability. To estimate the stability of networks, an original complex two-criterion coefficient was developed. The analysis of the ways to reduce the stability was carried out by measuring this coefficient in model and real networks. Thus, testing of the proposed methods confirmed their efficiency and enabled their application in various fields of science and technology, e.g., sociology, medicine, physics and radio engineering.https://ntv.ifmo.ru/file/article/20338.pdfvulnerabilitynetworkprincipal component analysiscentrality measuregraphpercolation |
| spellingShingle | Kirill V. Semenov Fedor L. Shuvaev Kirill I. Vitenzon An analysis of the ways to reduce the vulnerability of networks based on the sequential removal of key elements Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki vulnerability network principal component analysis centrality measure graph percolation |
| title | An analysis of the ways to reduce the vulnerability of networks based on the sequential removal of key elements |
| title_full | An analysis of the ways to reduce the vulnerability of networks based on the sequential removal of key elements |
| title_fullStr | An analysis of the ways to reduce the vulnerability of networks based on the sequential removal of key elements |
| title_full_unstemmed | An analysis of the ways to reduce the vulnerability of networks based on the sequential removal of key elements |
| title_short | An analysis of the ways to reduce the vulnerability of networks based on the sequential removal of key elements |
| title_sort | analysis of the ways to reduce the vulnerability of networks based on the sequential removal of key elements |
| topic | vulnerability network principal component analysis centrality measure graph percolation |
| url | https://ntv.ifmo.ru/file/article/20338.pdf |
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