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Morton Filter-Based Security Mechanism for Healthcare System in Cloud Computing

Electronic health records contain the patient’s sensitive information. If these data are acquired by a malicious user, it will not only cause the pilferage of the patient’s personal data but also affect the diagnosis and treatment. One of the most challenging tasks in cloud-based healthcare systems...

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Detalles Bibliográficos
Autores principales: Bhatia, Sugandh, Malhotra, Jyoteesh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8619796/
https://www.ncbi.nlm.nih.gov/pubmed/34828597
http://dx.doi.org/10.3390/healthcare9111551
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author Bhatia, Sugandh
Malhotra, Jyoteesh
author_facet Bhatia, Sugandh
Malhotra, Jyoteesh
author_sort Bhatia, Sugandh
collection PubMed
description Electronic health records contain the patient’s sensitive information. If these data are acquired by a malicious user, it will not only cause the pilferage of the patient’s personal data but also affect the diagnosis and treatment. One of the most challenging tasks in cloud-based healthcare systems is to provide security and privacy to electronic health records. Various probabilistic data structures and watermarking techniques were used in the cloud-based healthcare systems to secure patient’s data. Most of the existing studies focus on cuckoo and bloom filters, without considering their throughputs. In this research, a novel cloud security mechanism is introduced, which supersedes the shortcomings of existing approaches. The proposed solution enhances security with methods such as fragile watermark, least significant bit replacement watermarking, class reliability factor, and Morton filters included in the formation of the security mechanism. A Morton filter is an approximate set membership data structure (ASMDS) that proves many improvements to other data structures, such as cuckoo, bloom, semi-sorting cuckoo, and rank and select quotient filters. The Morton filter improves security; it supports insertions, deletions, and lookups operations and improves their respective throughputs by 0.9× to 15.5×, 1.3× to 1.6×, and 1.3× to 2.5×, when compared to cuckoo filters. We used Hadoop version 0.20.3, and the platform was Red Hat Enterprise Linux 6; we executed five experiments, and the average of the results has been taken. The results of the simulation work show that our proposed security mechanism provides an effective solution for secure data storage in cloud-based healthcare systems, with a load factor of 0.9. Furthermore, to aid cloud security in healthcare systems, we presented the motivation, objectives, related works, major research gaps, and materials and methods; we, thus, presented and implemented a cloud security mechanism, in the form of an algorithm and a set of results and conclusions.
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spelling pubmed-86197962021-11-27 Morton Filter-Based Security Mechanism for Healthcare System in Cloud Computing Bhatia, Sugandh Malhotra, Jyoteesh Healthcare (Basel) Article Electronic health records contain the patient’s sensitive information. If these data are acquired by a malicious user, it will not only cause the pilferage of the patient’s personal data but also affect the diagnosis and treatment. One of the most challenging tasks in cloud-based healthcare systems is to provide security and privacy to electronic health records. Various probabilistic data structures and watermarking techniques were used in the cloud-based healthcare systems to secure patient’s data. Most of the existing studies focus on cuckoo and bloom filters, without considering their throughputs. In this research, a novel cloud security mechanism is introduced, which supersedes the shortcomings of existing approaches. The proposed solution enhances security with methods such as fragile watermark, least significant bit replacement watermarking, class reliability factor, and Morton filters included in the formation of the security mechanism. A Morton filter is an approximate set membership data structure (ASMDS) that proves many improvements to other data structures, such as cuckoo, bloom, semi-sorting cuckoo, and rank and select quotient filters. The Morton filter improves security; it supports insertions, deletions, and lookups operations and improves their respective throughputs by 0.9× to 15.5×, 1.3× to 1.6×, and 1.3× to 2.5×, when compared to cuckoo filters. We used Hadoop version 0.20.3, and the platform was Red Hat Enterprise Linux 6; we executed five experiments, and the average of the results has been taken. The results of the simulation work show that our proposed security mechanism provides an effective solution for secure data storage in cloud-based healthcare systems, with a load factor of 0.9. Furthermore, to aid cloud security in healthcare systems, we presented the motivation, objectives, related works, major research gaps, and materials and methods; we, thus, presented and implemented a cloud security mechanism, in the form of an algorithm and a set of results and conclusions. MDPI 2021-11-15 /pmc/articles/PMC8619796/ /pubmed/34828597 http://dx.doi.org/10.3390/healthcare9111551 Text en © 2021 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
Bhatia, Sugandh
Malhotra, Jyoteesh
Morton Filter-Based Security Mechanism for Healthcare System in Cloud Computing
title Morton Filter-Based Security Mechanism for Healthcare System in Cloud Computing
title_full Morton Filter-Based Security Mechanism for Healthcare System in Cloud Computing
title_fullStr Morton Filter-Based Security Mechanism for Healthcare System in Cloud Computing
title_full_unstemmed Morton Filter-Based Security Mechanism for Healthcare System in Cloud Computing
title_short Morton Filter-Based Security Mechanism for Healthcare System in Cloud Computing
title_sort morton filter-based security mechanism for healthcare system in cloud computing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8619796/
https://www.ncbi.nlm.nih.gov/pubmed/34828597
http://dx.doi.org/10.3390/healthcare9111551
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