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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...

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Detalles Bibliográficos
Autores principales: Almalawi, Abdulmohsen, Khan, Asif Irshad, Alsolami, Fawaz, Abushark, Yoosef B., Alfakeeh, Ahmed S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
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.
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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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