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A novel medical image data protection scheme for smart healthcare system

Rehman, Mujeeb Ur; Shafique, Arslan; Khan, Muhammad Shahbaz; Driss, Maha; Boulila, Wadii; Ghadi, Yazeed Yasin; Changalasetty, Suresh Babu; Alhaisoni, Majed; Ahmad, Jawad

Authors

Mujeeb Ur Rehman

Arslan Shafique

Muhammad Shahbaz Khan

Maha Driss

Wadii Boulila

Yazeed Yasin Ghadi

Suresh Babu Changalasetty

Majed Alhaisoni



Abstract

The Internet of Multimedia Things (IoMT) refers to a network of interconnected multimedia devices that communicate with each other over the Internet. Recently, smart healthcare has emerged as a significant application of the IoMT, particularly in the context of knowledge‐based learning systems. Smart healthcare systems leverage knowledge‐based learning to become more context‐aware, adaptable, and auditable while maintaining the ability to learn from historical data. In smart healthcare systems, devices capture images, such as X‐rays, Magnetic Resonance Imaging. The security and integrity of these images are crucial for the databases used in knowledge‐based learning systems to foster structured decision‐making and enhance the learning abilities of AI. Moreover, in knowledge‐driven systems, the storage and transmission of HD medical images exert a burden on the limited bandwidth of the communication channel, leading to data transmission delays. To address the security and latency concerns, this paper presents a lightweight medical image encryption scheme utilising bit‐plane decomposition and chaos theory. The results of the experiment yield entropy, energy, and correlation values of 7.999, 0.0156, and 0.0001, respectively. This validates the effectiveness of the encryption system proposed in this paper, which offers high‐quality encryption, a large key space, key sensitivity, and resistance to statistical attacks.

Journal Article Type Article
Acceptance Date Oct 6, 2023
Online Publication Date Feb 13, 2024
Deposit Date Feb 19, 2024
Publicly Available Date Feb 19, 2024
Journal CAAI Transactions on Intelligence Technology
Print ISSN 2468-2322
Publisher Institution of Engineering and Technology (IET)
Peer Reviewed Peer Reviewed
DOI https://doi.org/10.1049/cit2.12292
Keywords data analysis, security, medical image processing
Public URL http://researchrepository.napier.ac.uk/Output/3514462

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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/

Copyright Statement
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.




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