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Authentication, access, and monitoring system for critical areas with the use of artificial intelligence integrated into perimeter security in a data center
Perimeter security in data centers helps protect systems and the data they store by preventing unauthorized access and protecting critical resources from potential threats. According to the report of the information security company SonicWall, in 2021, there was a 66% increase in the number of ranso...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10500307/ https://www.ncbi.nlm.nih.gov/pubmed/37719684 http://dx.doi.org/10.3389/fdata.2023.1200390 |
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author | Villegas-Ch, William García-Ortiz, Joselin |
author_facet | Villegas-Ch, William García-Ortiz, Joselin |
author_sort | Villegas-Ch, William |
collection | PubMed |
description | Perimeter security in data centers helps protect systems and the data they store by preventing unauthorized access and protecting critical resources from potential threats. According to the report of the information security company SonicWall, in 2021, there was a 66% increase in the number of ransomware attacks. In addition, the message from the same company indicates that the total number of cyber threats detected in 2021 increased by 24% compared to 2019. Among these attacks, the infrastructure of data centers was compromised; for this reason, organizations include elements Physical such as security cameras, movement detection systems, authentication systems, etc., as an additional measure that contributes to perimeter security. This work proposes using artificial intelligence in the perimeter security of data centers. It allows the automation and optimization of security processes, which translates into greater efficiency and reliability in the operations that prevent intrusions through authentication, permit verification, and monitoring critical areas. It is crucial to ensure that AI-based perimeter security systems are designed to protect and respect user privacy. In addition, it is essential to regularly monitor the effectiveness and integrity of these systems to ensure that they function correctly and meet security standards. |
format | Online Article Text |
id | pubmed-10500307 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-105003072023-09-15 Authentication, access, and monitoring system for critical areas with the use of artificial intelligence integrated into perimeter security in a data center Villegas-Ch, William García-Ortiz, Joselin Front Big Data Big Data Perimeter security in data centers helps protect systems and the data they store by preventing unauthorized access and protecting critical resources from potential threats. According to the report of the information security company SonicWall, in 2021, there was a 66% increase in the number of ransomware attacks. In addition, the message from the same company indicates that the total number of cyber threats detected in 2021 increased by 24% compared to 2019. Among these attacks, the infrastructure of data centers was compromised; for this reason, organizations include elements Physical such as security cameras, movement detection systems, authentication systems, etc., as an additional measure that contributes to perimeter security. This work proposes using artificial intelligence in the perimeter security of data centers. It allows the automation and optimization of security processes, which translates into greater efficiency and reliability in the operations that prevent intrusions through authentication, permit verification, and monitoring critical areas. It is crucial to ensure that AI-based perimeter security systems are designed to protect and respect user privacy. In addition, it is essential to regularly monitor the effectiveness and integrity of these systems to ensure that they function correctly and meet security standards. Frontiers Media S.A. 2023-08-31 /pmc/articles/PMC10500307/ /pubmed/37719684 http://dx.doi.org/10.3389/fdata.2023.1200390 Text en Copyright © 2023 Villegas-Ch and García-Ortiz. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Big Data Villegas-Ch, William García-Ortiz, Joselin Authentication, access, and monitoring system for critical areas with the use of artificial intelligence integrated into perimeter security in a data center |
title | Authentication, access, and monitoring system for critical areas with the use of artificial intelligence integrated into perimeter security in a data center |
title_full | Authentication, access, and monitoring system for critical areas with the use of artificial intelligence integrated into perimeter security in a data center |
title_fullStr | Authentication, access, and monitoring system for critical areas with the use of artificial intelligence integrated into perimeter security in a data center |
title_full_unstemmed | Authentication, access, and monitoring system for critical areas with the use of artificial intelligence integrated into perimeter security in a data center |
title_short | Authentication, access, and monitoring system for critical areas with the use of artificial intelligence integrated into perimeter security in a data center |
title_sort | authentication, access, and monitoring system for critical areas with the use of artificial intelligence integrated into perimeter security in a data center |
topic | Big Data |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10500307/ https://www.ncbi.nlm.nih.gov/pubmed/37719684 http://dx.doi.org/10.3389/fdata.2023.1200390 |
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