A formally verified authentication protocol in secure framework for mobile healthcare during COVID-19-like pandemic

Ahamad, Shaik Shakeel; Pathan, Al-Sakib Khan

doi:10.1080/09540091.2020.1854180

Cited by 23 publications

(12 citation statements)

References 30 publications

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“…The energy consumption by using the AES algorithm is 1.21 microjoule/byte. Figure 7 clearly shows the scheme outperformance from others based on the same platform, which is effective in securing the patient`s confidential data [ 25 ].…”

Section: State-of-the-art Reviewmentioning

confidence: 99%

Critical Retrospection of Performance of Emerging Mobile Technologies in Health Data Management

Vyas

Bhargava

Bhola

et al. 2022

Journal of Healthcare Engineering

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The recent advancement in mobile technologies has led to opening a new paradigm in the field of medical healthcare systems. The development of WBAN sensors, wearable devices, and 5G/6G wireless technology has made real-time monitoring and telecare of the patient feasible. The complex framework to secure sensitive data of the patient and healthcare professionals is critical. The fast computation of health data generated is crucial for disease prediction and trauma-related services; the security of data and financial transactions is also a major concern. Various models, algorithms, and frameworks have been developed to tame critical issues related to healthcare services. The efficiency of these frameworks and models depends on energy and time consumption. Thus, the review of recent emerging technologies in respect of energy and time consumption is required. This paper reviews the developments in recent mobile technologies, their application, and the comparative analysis of their performance parameters to explicitly understand the utility, capacity, and limitations. This will help to understand the shortcomings of the recent technologies for the development of better frameworks with higher performance capabilities as well as higher quality of services.

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Section: State-of-the-art Reviewmentioning

confidence: 99%

Critical Retrospection of Performance of Emerging Mobile Technologies in Health Data Management

Vyas

Bhargava

Bhola

et al. 2022

Journal of Healthcare Engineering

View full text Add to dashboard Cite

show abstract

“…There are also other concerns like excessive data collection, data usage policies and lack of user control [185] . The existing schemes employed in COVID-19 mobile health apps are not conforming the HIPAA (Health Insurance Portability and Accountability Act) and they are not providing enough end-to-end security [186] which make these mobile health apps vulnerable to many cyber risks.…”

Section: Challenges and Solutionsmentioning

confidence: 99%

A Survey on harnessing the Applications of Mobile Computing in Healthcare during the COVID-19 Pandemic: Challenges and Solutions

Ali

Khan

2023

Computer Networks

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“…Extensive simulation studies show that PDFS can boost the privacy security for data fusion in COVID-19 application environments based on IoMT while achieving high task classification precision, task completion rate, task data reliability, and task participation rate as well as a low average error rate. Using the trusted platform module, the authors suggested a group cloud architecture in an IoMT environment that guarantees end-to-end security and avoids many of the current negative aspects [37]. Authors in [38] proposed a configurable, reliable, and confidential distributed data storage scheme, which aims to encrypt the data and controlling the computing processes.…”

Section: Related Workmentioning

confidence: 99%

Energy-Efficient IoT e-Health Using Artificial Intelligence Model with Homomorphic Secret Sharing

et al. 2021

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Internet of Things (IoT) is a developing technology for supporting heterogeneous physical objects into smart things and improving the individuals living using wireless communication systems. Recently, many smart healthcare systems are based on the Internet of Medical Things (IoMT) to collect and analyze the data for infectious diseases, i.e., body fever, flu, COVID-19, shortness of breath, etc. with the least operation cost. However, the most important research challenges in such applications are storing the medical data on a secured cloud and make the disease diagnosis system more energy efficient. Additionally, the rapid explosion of IoMT technology has involved many cyber-criminals and continuous attempts to compromise medical devices with information loss and generating bogus certificates. Thus, the increase in modern technologies for healthcare applications based on IoMT, securing health data, and offering trusted communication against intruders is gaining much research attention. Therefore, this study aims to propose an energy-efficient IoT e-health model using artificial intelligence with homomorphic secret sharing, which aims to increase the maintainability of disease diagnosis systems and support trustworthy communication with the integration of the medical cloud. The proposed model is analyzed and proved its significance against relevant systems.

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A formally verified authentication protocol in secure framework for mobile healthcare during COVID-19-like pandemic

Cited by 23 publications

References 30 publications

Critical Retrospection of Performance of Emerging Mobile Technologies in Health Data Management

Critical Retrospection of Performance of Emerging Mobile Technologies in Health Data Management

A Survey on harnessing the Applications of Mobile Computing in Healthcare during the COVID-19 Pandemic: Challenges and Solutions

Energy-Efficient IoT e-Health Using Artificial Intelligence Model with Homomorphic Secret Sharing

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