An Energy-Efficient and Secure Data Inference Framework for Internet of Health Things: A Pilot Study

Kang, James Jin; Dibaei, Mahdi; Luo, Gang; Yang, Wencheng; Haskell‐Dowland, Paul; Zheng, Xi

doi:10.3390/s21010312

Cited by 13 publications

(3 citation statements)

References 22 publications

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“…Kang et al (2021) proposed a two-tier privacy-preserving data inference approach to reduce transmission data and battery usage from sensed data. Authors protected sensitive data from enemies [17]. Xu (2020) provided light-weight secure IoT (LS-IoT) with lightweight access control for real-time physical activity analysis for the physio net challenges database [18].…”

Section: Literature Surveymentioning

confidence: 99%

Analysis and Development of Security Framework for IOT Device

Shashi Kant Gupta

2023

tjjpt

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Internet of Things (IoT) devices are growing rapidly, making security and privacy crucial. This study analyses and develops an IoT-specific security framework. To address the specific security problems of IoT devices and provide effective techniques and measures to safeguard sensitive data, minimize vulnerabilities, and assure IoT system integrity. The analysis phase identifies and evaluates IoT ecosystem security issues such poor authentication, data encryption, susceptible firmware and software, and lack of standardization. The framework examines these difficulties to understand the security landscape and build effective countermeasures. The analysis informs the development phase, which includes device authentication and access control, data encryption and privacy protection, secure firmware and software upgrades, and standardization and compliance. These steps increase IoT device security by guaranteeing secure communication, data integrity, and protection against unauthorized access and assaults. This Paper Proposed security framework, to assure the security framework's originality and efficacy, it is developed methodically. IoT security literature, best practices, and upcoming technologies are researched extensively. The suggested security architecture is projected to improve IoT device trustworthiness and reliability, promoting their wider usage across domains and generating lightweight cryptography techniques. This analysis-driven and comprehensive methodology addresses security issues to help build secure and resilient IoT ecosystems.

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Section: Literature Surveymentioning

confidence: 99%

Analysis and Development of Security Framework for IOT Device

Shashi Kant Gupta

2023

tjjpt

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“…The energy problem is fundamental, especially with medical systems, as they are more demanding than other systems to save energy [ 120 ]. IoHT is highly dependent on the Internet of Things, and since the purposes of IoT are limited in resources, the issue of energy is also a real challenge facing medical systems and effective saving models must be proposed [ 22 , 121 ].…”

Section: Challenges In Ioht Domainmentioning

confidence: 99%

An empirical investigation into the altering health perspectives in the internet of health things

Bahbouh

Compte

Valdes

et al. 2022

Int. j. inf. tecnol.

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“…Technology such as mobile computing, body medical sensors, and communication is used for facilitating medical management these days [104]. This concept is defined as m-health in [105].…”

Section: Internet Of M-healthmentioning

confidence: 99%

Machine Learning and LPWAN Based Internet of Things Applications in Healthcare Sector during COVID-19 Pandemic

2021

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Low power wide area networks (LPWAN) are comprised of small devices having restricted processing resources and limited energy budget. These devices are connected with each other using communication protocols. Considering their available resources, these devices can be used in a number of different Internet of Things (IoT) applications. Another interesting paradigm is machine learning, which can also be integrated with LPWAN technology to embed intelligence into these IoT applications. These machine learning-based applications combine intelligence with LPWAN and prove to be a useful tool. One such IoT application is in the medical field, where they can be used to provide multiple services. In the scenario of the COVID-19 pandemic, the importance of LPWAN-based medical services has gained particular attention. This article describes various COVID-19-related healthcare services, using the the applications of machine learning and LPWAN in improving the medical domain during the current COVID-19 pandemic. We validate our idea with the help of a case study that describes a way to reduce the spread of any pandemic using LPWAN technology and machine learning. The case study compares k-Nearest Neighbors (KNN) and trust-based algorithms for mitigating the flow of virus spread. The simulation results show the effectiveness of KNN for curtailing the COVID-19 spread.

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An Energy-Efficient and Secure Data Inference Framework for Internet of Health Things: A Pilot Study

Cited by 13 publications

References 22 publications

Analysis and Development of Security Framework for IOT Device

Analysis and Development of Security Framework for IOT Device

An empirical investigation into the altering health perspectives in the internet of health things

Machine Learning and LPWAN Based Internet of Things Applications in Healthcare Sector during COVID-19 Pandemic

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