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Efficient Joint Key Authentication Model in E-Healthcare
1 Department of Computer Science, Air University Multan Campus, Multan, 60000, Pakistan
2 Faculty of Computing, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan
3 Department of Computer Science, COMSATS University Islamabad, Islamabad, Pakistan
4 Department of Computer Engineering, College of Computers and Information Technology, Taif University, Taif, Saudi Arabia
5 Faculty of Engineering, Moncton University, NB, E1A3E9, Canada
6 CES Laboratory, National School of Engineers of Sfax, University of Sfax, Sfax, 3038, Tunisia
7 Department of Information and Communication Engineering, Yeungnam University, Gyeongsan, 38541, Korea
* Corresponding Author: Muhammad Shafiq. Email:
Computers, Materials & Continua 2022, 71(2), 2739-2753. https://doi.org/10.32604/cmc.2022.022706
Received 16 August 2021; Accepted 27 September 2021; Issue published 07 December 2021
Abstract
Many patients have begun to use mobile applications to handle different health needs because they can better access high-speed Internet and smartphones. These devices and mobile applications are now increasingly used and integrated through the medical Internet of Things (mIoT). mIoT is an important part of the digital transformation of healthcare, because it can introduce new business models and allow efficiency improvements, cost control and improve patient experience. In the mIoT system, when migrating from traditional medical services to electronic medical services, patient protection and privacy are the priorities of each stakeholder. Therefore, it is recommended to use different user authentication and authorization methods to improve security and privacy. In this paper, our prosed model involves a shared identity verification process with different situations in the e-health system. We aim to reduce the strict and formal specification of the joint key authentication model. We use the AVISPA tool to verify through the well-known HLPSL specification language to develop user authentication and smart card use cases in a user-friendly environment. Our model has economic and strategic advantages for healthcare organizations and healthcare workers. The medical staff can increase their knowledge and ability to analyze medical data more easily. Our model can continuously track health indicators to automatically manage treatments and monitor health data in real time. Further, it can help customers prevent chronic diseases with the enhanced cognitive functions support. The necessity for efficient identity verification in e-health care is even more crucial for cognitive mitigation because we increasingly rely on mIoT systems.Keywords
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