Open Access

ARTICLE

Securing Healthcare Data in IoMT Network Using Enhanced Chaos Based Substitution and Diffusion

Musheer Ahmad¹, Reem Ibrahim Alkanhel^2,*, Naglaa F. Soliman², Abeer D. Algarni², Fathi E. Abd El-Samie³, Walid El-Shafai^3,4

1 Department of Computer Engineering, Jamia Millia Islamia, New Delhi, 110025, India
2 Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia
3 Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952, Egypt
4 Security Engineering Laboratory, Department of Computer Science, Prince Sultan University, Riyadh, 11586, Saudi Arabia

* Corresponding Author: Reem Ibrahim Alkanhel. Email:

Computer Systems Science and Engineering 2023, 47(2), 2361-2380. https://doi.org/10.32604/csse.2023.038439

Received 13 December 2022; Accepted 24 February 2023; Issue published 28 July 2023

Abstract

Patient privacy and data protection have been crucial concerns in E-healthcare systems for many years. In modern-day applications, patient data usually holds clinical imagery, records, and other medical details. Lately, the Internet of Medical Things (IoMT), equipped with cloud computing, has come out to be a beneficial paradigm in the healthcare field. However, the openness of networks and systems leads to security threats and illegal access. Therefore, reliable, fast, and robust security methods need to be developed to ensure the safe exchange of healthcare data generated from various image sensing and other IoMT-driven devices in the IoMT network. This paper presents an image protection scheme for healthcare applications to protect patients’ medical image data exchanged in IoMT networks. The proposed security scheme depends on an enhanced 2D discrete chaotic map and allows dynamic substitution based on an optimized highly-nonlinear S-box and diffusion to gain an excellent security performance. The optimized S-box has an excellent nonlinearity score of 112. The new image protection scheme is efficient enough to exhibit correlation values less than 0.0022, entropy values higher than 7.999, and NPCR values around 99.6%. To reveal the efficacy of the scheme, several comparison studies are presented. These comparison studies reveal that the novel protection scheme is robust, efficient, and capable of securing healthcare imagery in IoMT systems.

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Keywords

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