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Modeling of Anti-tracking Network Based on Convex-Polytope Topology
Anti-tracking network plays an important role in protection of network users’ identities and communication privacy. Confronted with the frequent network attacks or infiltration to anti-tracking network, a robust and destroy-resistant network topology is an important prerequisite to maintain the stab...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7302821/ http://dx.doi.org/10.1007/978-3-030-50417-5_32 |
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author | Tian, Changbo Zhang, Yongzheng Yin, Tao |
author_facet | Tian, Changbo Zhang, Yongzheng Yin, Tao |
author_sort | Tian, Changbo |
collection | PubMed |
description | Anti-tracking network plays an important role in protection of network users’ identities and communication privacy. Confronted with the frequent network attacks or infiltration to anti-tracking network, a robust and destroy-resistant network topology is an important prerequisite to maintain the stability and security of anti-tracking network. From the aspects of network stability, network resilience and destroy-resistance, we propose the convex-polytope topology (CPT) applied in the anti-tracking network. CPT has three main advantages: (1) CPT can easily avoid the threat of key nodes and cut vertices to network structure; (2) Even the nodes could randomly join in or quit the network, CPT can easily keep the network topology in stable structure without the global view of network; (3) CPT can easily achieve the self-optimization of network topology. Anti-tracking network based on CPT can achieve the self-maintenance and self-optimization of its network topology. We compare CPT with other methods of topology optimization. From the experimental results, CPT has better robustness, resilience and destroy-resistance confronted with dynamically changed topology, and performs better in the efficiency of network self-optimization. |
format | Online Article Text |
id | pubmed-7302821 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-73028212020-06-19 Modeling of Anti-tracking Network Based on Convex-Polytope Topology Tian, Changbo Zhang, Yongzheng Yin, Tao Computational Science – ICCS 2020 Article Anti-tracking network plays an important role in protection of network users’ identities and communication privacy. Confronted with the frequent network attacks or infiltration to anti-tracking network, a robust and destroy-resistant network topology is an important prerequisite to maintain the stability and security of anti-tracking network. From the aspects of network stability, network resilience and destroy-resistance, we propose the convex-polytope topology (CPT) applied in the anti-tracking network. CPT has three main advantages: (1) CPT can easily avoid the threat of key nodes and cut vertices to network structure; (2) Even the nodes could randomly join in or quit the network, CPT can easily keep the network topology in stable structure without the global view of network; (3) CPT can easily achieve the self-optimization of network topology. Anti-tracking network based on CPT can achieve the self-maintenance and self-optimization of its network topology. We compare CPT with other methods of topology optimization. From the experimental results, CPT has better robustness, resilience and destroy-resistance confronted with dynamically changed topology, and performs better in the efficiency of network self-optimization. 2020-06-15 /pmc/articles/PMC7302821/ http://dx.doi.org/10.1007/978-3-030-50417-5_32 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Tian, Changbo Zhang, Yongzheng Yin, Tao Modeling of Anti-tracking Network Based on Convex-Polytope Topology |
title | Modeling of Anti-tracking Network Based on Convex-Polytope Topology |
title_full | Modeling of Anti-tracking Network Based on Convex-Polytope Topology |
title_fullStr | Modeling of Anti-tracking Network Based on Convex-Polytope Topology |
title_full_unstemmed | Modeling of Anti-tracking Network Based on Convex-Polytope Topology |
title_short | Modeling of Anti-tracking Network Based on Convex-Polytope Topology |
title_sort | modeling of anti-tracking network based on convex-polytope topology |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7302821/ http://dx.doi.org/10.1007/978-3-030-50417-5_32 |
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