A secure remote health monitoring model for early disease diagnosis in cloud-based IoT environment
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ORIGINAL ARTICLE
A secure remote health monitoring model for early disease diagnosis in cloud-based IoT environment Samira Akhbarifar 1 & Hamid Haj Seyyed Javadi 2
&
Amir Masoud Rahmani 1 & Mehdi Hosseinzadeh 3,4
Received: 13 July 2020 / Accepted: 12 October 2020 # Springer-Verlag London Ltd., part of Springer Nature 2020
Abstract Internet of Things (IoT) and smart medical devices have improved the healthcare systems by enabling remote monitoring and screening of the patients’ health conditions anywhere and anytime. Due to an unexpected and huge increasing in number of patients during coronavirus (novel COVID-19) pandemic, it is considerably indispensable to monitor patients’ health condition continuously before any serious disorder or infection occur. According to transferring the huge volume of produced sensitive health data of patients who do not want their private medical information to be revealed, dealing with security issues of IoT data as a major concern and a challenging problem has remained yet. Encountering this challenge, in this paper, a remote health monitoring model that applies a lightweight block encryption method for provisioning security for health and medical data in cloud-based IoT environment is presented. In this model, the patients’ health statuses are determined via predicting critical situations through data mining methods for analyzing their biological data sensed by smart medical IoT devices in which a lightweight secure block encryption technique is used to ensure the patients’ sensitive data become protected. Lightweight block encryption methods have a crucial effective influence on this sort of systems due to the restricted resources in IoT platforms. Experimental outcomes show that K-star classification method achieves the best results among RF, MLP, SVM, and J48 classifiers, with accuracy of 95%, precision of 94.5%, recall of 93.5%, and f-score of 93.99%. Therefore, regarding the attained outcomes, the suggested model is successful in achieving an effective remote health monitoring model assisted by secure IoT data in cloud-based IoT platforms. Keywords Internet of Things . Security . Block encryption . Health monitoring systems . Data mining
1 Introduction In patients with novel COVID-19, there is an extraordinary rate of cardiovascular disease (CVD), and more than 7% of patients are involved with myocardial injury from the * Hamid Haj Seyyed Javadi [email protected] Mehdi Hosseinzadeh [email protected] 1
Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
2
Department of Mathematics and Computer Science, Shahed University, Tehran, Iran
3
Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam
4
Mental Health Research Center, Psychosocial Health Research Institue, Iran University of Medical Sciences, Tehran, Iran
infection (22% of critically ill patients). The presence of novel COVID-19 increased the risk of death in CVD patients [1, 2]. Many already published and relevant arti
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