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Managing Security of Healthcare Data for a Modern Healthcare System
The advent of Artificial Intelligence (AI) and the Internet of Things (IoT) have recently created previously unimaginable opportunities for boosting clinical and patient services, reducing costs and improving community health. Yet, a fundamental challenge that the modern healthcare management system...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10098823/ https://www.ncbi.nlm.nih.gov/pubmed/37050672 http://dx.doi.org/10.3390/s23073612 |
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author | Almalawi, Abdulmohsen Khan, Asif Irshad Alsolami, Fawaz Abushark, Yoosef B. Alfakeeh, Ahmed S. |
author_facet | Almalawi, Abdulmohsen Khan, Asif Irshad Alsolami, Fawaz Abushark, Yoosef B. Alfakeeh, Ahmed S. |
author_sort | Almalawi, Abdulmohsen |
collection | PubMed |
description | The advent of Artificial Intelligence (AI) and the Internet of Things (IoT) have recently created previously unimaginable opportunities for boosting clinical and patient services, reducing costs and improving community health. Yet, a fundamental challenge that the modern healthcare management system faces is storing and securely transferring data. Therefore, this research proposes a novel Lionized remora optimization-based serpent (LRO-S) encryption method to encrypt sensitive data and reduce privacy breaches and cyber-attacks from unauthorized users and hackers. The LRO-S method is the combination of hybrid metaheuristic optimization and improved security algorithm. The fitness functions of lion and remora are combined to create a new algorithm for security key generation, which is provided to the serpent encryption algorithm. The LRO-S technique encrypts sensitive patient data before storing it in the cloud. The primary goal of this study is to improve the safety and adaptability of medical professionals’ access to cloud-based patient-sensitive data more securely. The experiment’s findings suggest that the secret keys generated are sufficiently random and one of a kind to provide adequate protection for the data stored in modern healthcare management systems. The proposed method minimizes the time needed to encrypt and decrypt data and improves privacy standards. This study found that the suggested technique outperformed previous techniques in terms of reducing execution time and is cost-effective. |
format | Online Article Text |
id | pubmed-10098823 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100988232023-04-14 Managing Security of Healthcare Data for a Modern Healthcare System Almalawi, Abdulmohsen Khan, Asif Irshad Alsolami, Fawaz Abushark, Yoosef B. Alfakeeh, Ahmed S. Sensors (Basel) Article The advent of Artificial Intelligence (AI) and the Internet of Things (IoT) have recently created previously unimaginable opportunities for boosting clinical and patient services, reducing costs and improving community health. Yet, a fundamental challenge that the modern healthcare management system faces is storing and securely transferring data. Therefore, this research proposes a novel Lionized remora optimization-based serpent (LRO-S) encryption method to encrypt sensitive data and reduce privacy breaches and cyber-attacks from unauthorized users and hackers. The LRO-S method is the combination of hybrid metaheuristic optimization and improved security algorithm. The fitness functions of lion and remora are combined to create a new algorithm for security key generation, which is provided to the serpent encryption algorithm. The LRO-S technique encrypts sensitive patient data before storing it in the cloud. The primary goal of this study is to improve the safety and adaptability of medical professionals’ access to cloud-based patient-sensitive data more securely. The experiment’s findings suggest that the secret keys generated are sufficiently random and one of a kind to provide adequate protection for the data stored in modern healthcare management systems. The proposed method minimizes the time needed to encrypt and decrypt data and improves privacy standards. This study found that the suggested technique outperformed previous techniques in terms of reducing execution time and is cost-effective. MDPI 2023-03-30 /pmc/articles/PMC10098823/ /pubmed/37050672 http://dx.doi.org/10.3390/s23073612 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Almalawi, Abdulmohsen Khan, Asif Irshad Alsolami, Fawaz Abushark, Yoosef B. Alfakeeh, Ahmed S. Managing Security of Healthcare Data for a Modern Healthcare System |
title | Managing Security of Healthcare Data for a Modern Healthcare System |
title_full | Managing Security of Healthcare Data for a Modern Healthcare System |
title_fullStr | Managing Security of Healthcare Data for a Modern Healthcare System |
title_full_unstemmed | Managing Security of Healthcare Data for a Modern Healthcare System |
title_short | Managing Security of Healthcare Data for a Modern Healthcare System |
title_sort | managing security of healthcare data for a modern healthcare system |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10098823/ https://www.ncbi.nlm.nih.gov/pubmed/37050672 http://dx.doi.org/10.3390/s23073612 |
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