ANAF-IoMT: A Novel Architectural Framework for IoMT-Enabled Smart Healthcare System by Enhancing Security Based on RECC-VC

The Internet of Medical Things (IoMT) is an arising trend that provides a significant amount of efficient and effective services for patients as well as healthcare professionals for the treatment of disparate diseases. The IoMT has numerous benefits; however, the security issue still persists as a c...

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Veröffentlicht in:IEEE transactions on industrial informatics 2022-12, Vol.18 (12), p.8936-8943
Hauptverfasser: Kumar, Mohit, Kavita, Verma, Sahil, Kumar, Ashwani, Ijaz, Muhammad Fazal, Rawat, Danda B.
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container_end_page 8943
container_issue 12
container_start_page 8936
container_title IEEE transactions on industrial informatics
container_volume 18
creator Kumar, Mohit
Kavita
Verma, Sahil
Kumar, Ashwani
Ijaz, Muhammad Fazal
Rawat, Danda B.
description The Internet of Medical Things (IoMT) is an arising trend that provides a significant amount of efficient and effective services for patients as well as healthcare professionals for the treatment of disparate diseases. The IoMT has numerous benefits; however, the security issue still persists as a challenge. The lack of security awareness among novice IoMT users and the risk of several intermediary attacks for accessing health information severely endanger the use of IoMT. In this article, rooted elliptic curve cryptography with Vigenère cipher (RECC-VC) centered security amelioration on the IoMT is proposed for enhancing security. First, this work utilizes the exponential K-anonymity algorithm for privacy preservation. Second, a new improved Elman neural network (IENN) is proposed for analyzing the sensitivity level of data. The Gaussian mutated chimp optimization is employed for weight updating in this IENN. Finally, a novel RECC-VC is proposed for securely uploading the data to the cloud server. Additionally, data are stored in the cloud server using blockchain technology. In experimental analysis, the proposed methodologies attain better results than the prevailing methods. The proposed IENN model achieves an accuracy of 96% and is validated against state-of-the-art methods. Also, the proposed RECC-VC attains 98% of the security level.
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source IEEE Electronic Library (IEL)
subjects Algorithms
Authentication
Blockchain technology
Cryptography
Curves
Electronic mail
Encryption
exponential K-anonymity (EKA)
Gaussian mutated chimp optimization (GMCO)
Health care
improved Elman neural network (IENN)
Internet of medical things
Internet of Medical Things (IoMT)
Internet of Things
Monitoring
Neural networks
Optimization
Privacy
rooted elliptic curve cryptography with Vigenère cipher (RECC-VC)
Security
Sensors
Servers
title ANAF-IoMT: A Novel Architectural Framework for IoMT-Enabled Smart Healthcare System by Enhancing Security Based on RECC-VC
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