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Improved Handover Authentication in Fifth-Generation Communication Networks Using Fuzzy Evolutionary Optimisation with Nanocore Elements in Mobile Healthcare Applications
Authentication is a suitable form of restricting the network from different types of attacks, especially in case of fifth-generation telecommunication networks, especially in healthcare applications. The handover and authentication mechanism are one such type that enables mitigation of attacks in he...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8759874/ https://www.ncbi.nlm.nih.gov/pubmed/35035816 http://dx.doi.org/10.1155/2022/2500377 |
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author | Divakaran, J. Prashanth, S. K. Mohammad, Gouse Baig Shitharth, Dr Mohanty, Sachi Nandan Arvind, C. Srihari, K. Abdullah R., Yasir Sundramurthy, Venkatesa Prabhu |
author_facet | Divakaran, J. Prashanth, S. K. Mohammad, Gouse Baig Shitharth, Dr Mohanty, Sachi Nandan Arvind, C. Srihari, K. Abdullah R., Yasir Sundramurthy, Venkatesa Prabhu |
author_sort | Divakaran, J. |
collection | PubMed |
description | Authentication is a suitable form of restricting the network from different types of attacks, especially in case of fifth-generation telecommunication networks, especially in healthcare applications. The handover and authentication mechanism are one such type that enables mitigation of attacks in health-related services. In this paper, we model an evolutionary model that uses a fuzzy evolutionary model in maintaining the handover and key management to improve the performance of authentication in nanocore technology-based 5G networks. The model is designed in such a way that it minimizes the delays and complexity while authenticating the networks in 5G networks. The attacks are mitigated using an evolutionary model when it is trained with the relevant attack datasets, and the model is validated to mitigate the attacks. The simulation is conducted to test the efficacy of the model, and the results of simulation show that the proposed method is effective in improving the handling and authentication and mitigation against various types of attacks in mobile health applications. |
format | Online Article Text |
id | pubmed-8759874 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-87598742022-01-15 Improved Handover Authentication in Fifth-Generation Communication Networks Using Fuzzy Evolutionary Optimisation with Nanocore Elements in Mobile Healthcare Applications Divakaran, J. Prashanth, S. K. Mohammad, Gouse Baig Shitharth, Dr Mohanty, Sachi Nandan Arvind, C. Srihari, K. Abdullah R., Yasir Sundramurthy, Venkatesa Prabhu J Healthc Eng Research Article Authentication is a suitable form of restricting the network from different types of attacks, especially in case of fifth-generation telecommunication networks, especially in healthcare applications. The handover and authentication mechanism are one such type that enables mitigation of attacks in health-related services. In this paper, we model an evolutionary model that uses a fuzzy evolutionary model in maintaining the handover and key management to improve the performance of authentication in nanocore technology-based 5G networks. The model is designed in such a way that it minimizes the delays and complexity while authenticating the networks in 5G networks. The attacks are mitigated using an evolutionary model when it is trained with the relevant attack datasets, and the model is validated to mitigate the attacks. The simulation is conducted to test the efficacy of the model, and the results of simulation show that the proposed method is effective in improving the handling and authentication and mitigation against various types of attacks in mobile health applications. Hindawi 2022-01-07 /pmc/articles/PMC8759874/ /pubmed/35035816 http://dx.doi.org/10.1155/2022/2500377 Text en Copyright © 2022 J. Divakaran et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Divakaran, J. Prashanth, S. K. Mohammad, Gouse Baig Shitharth, Dr Mohanty, Sachi Nandan Arvind, C. Srihari, K. Abdullah R., Yasir Sundramurthy, Venkatesa Prabhu Improved Handover Authentication in Fifth-Generation Communication Networks Using Fuzzy Evolutionary Optimisation with Nanocore Elements in Mobile Healthcare Applications |
title | Improved Handover Authentication in Fifth-Generation Communication Networks Using Fuzzy Evolutionary Optimisation with Nanocore Elements in Mobile Healthcare Applications |
title_full | Improved Handover Authentication in Fifth-Generation Communication Networks Using Fuzzy Evolutionary Optimisation with Nanocore Elements in Mobile Healthcare Applications |
title_fullStr | Improved Handover Authentication in Fifth-Generation Communication Networks Using Fuzzy Evolutionary Optimisation with Nanocore Elements in Mobile Healthcare Applications |
title_full_unstemmed | Improved Handover Authentication in Fifth-Generation Communication Networks Using Fuzzy Evolutionary Optimisation with Nanocore Elements in Mobile Healthcare Applications |
title_short | Improved Handover Authentication in Fifth-Generation Communication Networks Using Fuzzy Evolutionary Optimisation with Nanocore Elements in Mobile Healthcare Applications |
title_sort | improved handover authentication in fifth-generation communication networks using fuzzy evolutionary optimisation with nanocore elements in mobile healthcare applications |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8759874/ https://www.ncbi.nlm.nih.gov/pubmed/35035816 http://dx.doi.org/10.1155/2022/2500377 |
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