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Developing Secure Healthcare Video Consultations for Corona Virus (COVID-19) Pandemic

Mohammed A. AlZain1,*, Jehad F. Al-Amri1, Ahmed I. Sallam2, Emad Sami Jaha3, Sultan S. Alshamrani1, Hala S. El-Sayed4, Osama S. Faragallah1

1 Department of Information Technology, College of Computers and Information Technology, Taif University, P.O. 11099, Taif 21944, Saudi Arabia
2 Department of Computer Science and Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf 32952, Egypt
3 Department of Computer Science, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia
4 Department of Electrical Engineering, Faculty of Engineering, Menoufia University, Shebin El-Kom 32511, Egypt

* Corresponding Author: Mohammed A. AlZain. Email: email

Intelligent Automation & Soft Computing 2022, 31(3), 1627-1640. https://doi.org/10.32604/iasc.2022.020137

Abstract

Many health networks became increasingly interactive in implementing a consulting approach to telemedicine before the COVID-19 pandemic. To mitigate patient trafficking and reduce the virus exposure in health centers, several GPs, physicians and people in the video were consulted during the pandemic at the start. Video and smartphone consultations will allow well-insulated and high-risk medical practitioners to maintain their patient care security. Video appointments include diabetes, obesity, hypertension, stroke, mental health, chemotherapy and chronic pain. Many urgent diseases, including an emergency triage for the eye, may also be used for online consultations and triages. The COVID-19 pandemic shows that healthcare option for healthy healthcare and the potential to increase to a minimum, such as video consultations, have grown quickly. The dissemination of COVID-19 viruses now aims at extending the use of Video-Health Consultations by exchanging insights and simulations of health consultations and saving costs and healthcare practices as a consequence of the COVID-19 pandemic. Our paper focuses on video consulting privacy. This essay further presents the advantages and inconveniences of video consultation and its implementation.‏ This paper suggests the most recent video encryption method known as high efficiency video coding selective encryption (HEVC SE). Our video consultation schema has been improved to secure video streaming on a low calculation overhead, with the same bit rate and to ensure compatibility with the video format. The contribution is made with RC5, a low complexity computer, to encrypt subsets of bin-strings binarized in the HEVC sense using the context-adaptive binary arithmetic coding (CABAC) method through the bypass binary arithmetic coding. This sequence of binstrings consists of a non-zero differential transforming cosine (DCT) coefficient bit, MVD sign bits, remainder absolute DCT suffixes and absolute MVD suffixes. This paper also examines the efficiency assessment of the use of the RC5 with its modes of operations in the HEVC CABAC SE proposed. This study chooses the best operating mode for RC5 to be used for the healthcare video consultation application. Security analysis, such as histogram analysis, correlation coefficient testing and key sensitivity testing, is presented to protect against brute force and statistical attacks for the proposed schema.

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Cite This Article

APA Style
AlZain, M.A., Al-Amri, J.F., Sallam, A.I., Jaha, E.S., Alshamrani, S.S. et al. (2022). Developing secure healthcare video consultations for corona virus (COVID-19) pandemic. Intelligent Automation & Soft Computing, 31(3), 1627-1640. https://doi.org/10.32604/iasc.2022.020137
Vancouver Style
AlZain MA, Al-Amri JF, Sallam AI, Jaha ES, Alshamrani SS, El-Sayed HS, et al. Developing secure healthcare video consultations for corona virus (COVID-19) pandemic. Intell Automat Soft Comput . 2022;31(3):1627-1640 https://doi.org/10.32604/iasc.2022.020137
IEEE Style
M.A. AlZain et al., "Developing Secure Healthcare Video Consultations for Corona Virus (COVID-19) Pandemic," Intell. Automat. Soft Comput. , vol. 31, no. 3, pp. 1627-1640. 2022. https://doi.org/10.32604/iasc.2022.020137



cc Copyright © 2022 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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