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BBNSF: Blockchain-Based Novel Secure Framework Using RP(2)-RSA and ASR-ANN Technique for IoT Enabled Healthcare Systems

The wearable healthcare equipment is primarily designed to alert patients of any specific health conditions or to act as a useful tool for treatment or follow-up. With the growth of technologies and connectivity, the security of these devices has become a growing concern. The lack of security awaren...

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Autores principales: Kumar, Mohit, Mukherjee, Priya, Verma, Sahil, Kavita, Kaur, Maninder, Singh, S., Kobielnik, Martyna, Woźniak, Marcin, Shafi, Jana, Ijaz, Muhammad Fazal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9738425/
https://www.ncbi.nlm.nih.gov/pubmed/36502150
http://dx.doi.org/10.3390/s22239448
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author Kumar, Mohit
Mukherjee, Priya
Verma, Sahil
Kavita,
Kaur, Maninder
Singh, S.
Kobielnik, Martyna
Woźniak, Marcin
Shafi, Jana
Ijaz, Muhammad Fazal
author_facet Kumar, Mohit
Mukherjee, Priya
Verma, Sahil
Kavita,
Kaur, Maninder
Singh, S.
Kobielnik, Martyna
Woźniak, Marcin
Shafi, Jana
Ijaz, Muhammad Fazal
author_sort Kumar, Mohit
collection PubMed
description The wearable healthcare equipment is primarily designed to alert patients of any specific health conditions or to act as a useful tool for treatment or follow-up. With the growth of technologies and connectivity, the security of these devices has become a growing concern. The lack of security awareness amongst novice users and the risk of several intermediary attacks for accessing health information severely endangers the use of IoT-enabled healthcare systems. In this paper, a blockchain-based secure data storage system is proposed along with a user authentication and health status prediction system. Firstly, this work utilizes reversed public-private keys combined Rivest–Shamir–Adleman (RP(2)-RSA) algorithm for providing security. Secondly, feature selection is completed by employing the correlation factor-induced salp swarm optimization algorithm (CF-SSOA). Finally, health status classification is performed using advanced weight initialization adapted SignReLU activation function-based artificial neural network (ASR-ANN) which classifies the status as normal and abnormal. Meanwhile, the abnormal measures are stored in the corresponding patient blockchain. Here, blockchain technology is used to store medical data securely for further analysis. The proposed model has achieved an accuracy of 95.893% and is validated by comparing it with other baseline techniques. On the security front, the proposed RP(2)-RSA attains a 96.123% security level.
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spelling pubmed-97384252022-12-11 BBNSF: Blockchain-Based Novel Secure Framework Using RP(2)-RSA and ASR-ANN Technique for IoT Enabled Healthcare Systems Kumar, Mohit Mukherjee, Priya Verma, Sahil Kavita, Kaur, Maninder Singh, S. Kobielnik, Martyna Woźniak, Marcin Shafi, Jana Ijaz, Muhammad Fazal Sensors (Basel) Article The wearable healthcare equipment is primarily designed to alert patients of any specific health conditions or to act as a useful tool for treatment or follow-up. With the growth of technologies and connectivity, the security of these devices has become a growing concern. The lack of security awareness amongst novice users and the risk of several intermediary attacks for accessing health information severely endangers the use of IoT-enabled healthcare systems. In this paper, a blockchain-based secure data storage system is proposed along with a user authentication and health status prediction system. Firstly, this work utilizes reversed public-private keys combined Rivest–Shamir–Adleman (RP(2)-RSA) algorithm for providing security. Secondly, feature selection is completed by employing the correlation factor-induced salp swarm optimization algorithm (CF-SSOA). Finally, health status classification is performed using advanced weight initialization adapted SignReLU activation function-based artificial neural network (ASR-ANN) which classifies the status as normal and abnormal. Meanwhile, the abnormal measures are stored in the corresponding patient blockchain. Here, blockchain technology is used to store medical data securely for further analysis. The proposed model has achieved an accuracy of 95.893% and is validated by comparing it with other baseline techniques. On the security front, the proposed RP(2)-RSA attains a 96.123% security level. MDPI 2022-12-02 /pmc/articles/PMC9738425/ /pubmed/36502150 http://dx.doi.org/10.3390/s22239448 Text en © 2022 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
Kumar, Mohit
Mukherjee, Priya
Verma, Sahil
Kavita,
Kaur, Maninder
Singh, S.
Kobielnik, Martyna
Woźniak, Marcin
Shafi, Jana
Ijaz, Muhammad Fazal
BBNSF: Blockchain-Based Novel Secure Framework Using RP(2)-RSA and ASR-ANN Technique for IoT Enabled Healthcare Systems
title BBNSF: Blockchain-Based Novel Secure Framework Using RP(2)-RSA and ASR-ANN Technique for IoT Enabled Healthcare Systems
title_full BBNSF: Blockchain-Based Novel Secure Framework Using RP(2)-RSA and ASR-ANN Technique for IoT Enabled Healthcare Systems
title_fullStr BBNSF: Blockchain-Based Novel Secure Framework Using RP(2)-RSA and ASR-ANN Technique for IoT Enabled Healthcare Systems
title_full_unstemmed BBNSF: Blockchain-Based Novel Secure Framework Using RP(2)-RSA and ASR-ANN Technique for IoT Enabled Healthcare Systems
title_short BBNSF: Blockchain-Based Novel Secure Framework Using RP(2)-RSA and ASR-ANN Technique for IoT Enabled Healthcare Systems
title_sort bbnsf: blockchain-based novel secure framework using rp(2)-rsa and asr-ann technique for iot enabled healthcare systems
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9738425/
https://www.ncbi.nlm.nih.gov/pubmed/36502150
http://dx.doi.org/10.3390/s22239448
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