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Smart healthcare system using integrated and lightweight ECC with private blockchain for multimedia medical data processing

Cloud-based Healthcare 4.0 systems have research challenges with secure medical data processing, especially biomedical image processing with privacy protection. Medical records are generally text/numerical or multimedia. Multimedia data includes X-ray scans, Computed Tomography (CT) scans, Magnetic...

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Detalles Bibliográficos
Autores principales: Mahajan, Hemant B., Junnarkar, Aparna A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10105161/
https://www.ncbi.nlm.nih.gov/pubmed/37362704
http://dx.doi.org/10.1007/s11042-023-15204-4
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author Mahajan, Hemant B.
Junnarkar, Aparna A.
author_facet Mahajan, Hemant B.
Junnarkar, Aparna A.
author_sort Mahajan, Hemant B.
collection PubMed
description Cloud-based Healthcare 4.0 systems have research challenges with secure medical data processing, especially biomedical image processing with privacy protection. Medical records are generally text/numerical or multimedia. Multimedia data includes X-ray scans, Computed Tomography (CT) scans, Magnetic Resonance Imaging (MRI) scans, etc. Transferring biomedical multimedia data to medical authorities raises various security concerns. This paper proposes a one-of-a-kind blockchain-based secure biomedical image processing system that maintains anonymity. The integrated Healthcare 4.0 assisted multimedia image processing architecture includes an edge layer, fog computing layer, cloud storage layer, and blockchain layer. The edge layer collects and sends periodic medical information from the patient to the higher layer. The multimedia data from the edge layer is securely preserved in blockchain-assisted cloud storage through fog nodes using lightweight cryptography. Medical users then safely search such data for medical treatment or monitoring. Lightweight cryptographic procedures are proposed by employing Elliptic Curve Cryptography (ECC) with Elliptic Curve Diffie-Hellman (ECDH) and Elliptic Curve Digital Signature (ECDS) algorithm to secure biomedical image processing while maintaining privacy (ECDSA). The proposed technique is experimented with using publically available chest X-ray and CT images. The experimental results revealed that the proposed model shows higher computational efficiency (encryption and decryption time), Peak to Signal Noise Ratio (PSNR), and Meas Square Error (MSE).
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spelling pubmed-101051612023-04-17 Smart healthcare system using integrated and lightweight ECC with private blockchain for multimedia medical data processing Mahajan, Hemant B. Junnarkar, Aparna A. Multimed Tools Appl Article Cloud-based Healthcare 4.0 systems have research challenges with secure medical data processing, especially biomedical image processing with privacy protection. Medical records are generally text/numerical or multimedia. Multimedia data includes X-ray scans, Computed Tomography (CT) scans, Magnetic Resonance Imaging (MRI) scans, etc. Transferring biomedical multimedia data to medical authorities raises various security concerns. This paper proposes a one-of-a-kind blockchain-based secure biomedical image processing system that maintains anonymity. The integrated Healthcare 4.0 assisted multimedia image processing architecture includes an edge layer, fog computing layer, cloud storage layer, and blockchain layer. The edge layer collects and sends periodic medical information from the patient to the higher layer. The multimedia data from the edge layer is securely preserved in blockchain-assisted cloud storage through fog nodes using lightweight cryptography. Medical users then safely search such data for medical treatment or monitoring. Lightweight cryptographic procedures are proposed by employing Elliptic Curve Cryptography (ECC) with Elliptic Curve Diffie-Hellman (ECDH) and Elliptic Curve Digital Signature (ECDS) algorithm to secure biomedical image processing while maintaining privacy (ECDSA). The proposed technique is experimented with using publically available chest X-ray and CT images. The experimental results revealed that the proposed model shows higher computational efficiency (encryption and decryption time), Peak to Signal Noise Ratio (PSNR), and Meas Square Error (MSE). Springer US 2023-04-15 /pmc/articles/PMC10105161/ /pubmed/37362704 http://dx.doi.org/10.1007/s11042-023-15204-4 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Mahajan, Hemant B.
Junnarkar, Aparna A.
Smart healthcare system using integrated and lightweight ECC with private blockchain for multimedia medical data processing
title Smart healthcare system using integrated and lightweight ECC with private blockchain for multimedia medical data processing
title_full Smart healthcare system using integrated and lightweight ECC with private blockchain for multimedia medical data processing
title_fullStr Smart healthcare system using integrated and lightweight ECC with private blockchain for multimedia medical data processing
title_full_unstemmed Smart healthcare system using integrated and lightweight ECC with private blockchain for multimedia medical data processing
title_short Smart healthcare system using integrated and lightweight ECC with private blockchain for multimedia medical data processing
title_sort smart healthcare system using integrated and lightweight ecc with private blockchain for multimedia medical data processing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10105161/
https://www.ncbi.nlm.nih.gov/pubmed/37362704
http://dx.doi.org/10.1007/s11042-023-15204-4
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