A Secure Framework for IoT-Based Healthcare System

Chattopadhyay, Arup Kumar; Nag, Amitava; Ghosh, Debalina; Chanda, Koustav

doi:10.1007/978-981-13-1544-2_31

Cited by 15 publications

(13 citation statements)

References 13 publications

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“…Medical Devices Based on IOT/IOMT-are uploading and analysing data in real time; used for quarantined self to telemonitoring/teleICU consultation to AI predication from sepsis (32,33). There are AI enabled devices like wheelchairs-sensor for automatic parking of wheelchairs (34), thermometer, weighing scale, ECG (35).…”

Section: Ai In Screeningmentioning

confidence: 99%

Use of artificial intelligence in healthcare delivery in India

Pradhan¹,

John²,

Sandhu³

2021

J Hosp Manag Health Policy

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The growth of artificial intelligence (AI) has seen an exponential growth in India. Recent policy initiatives favouring the acceleration of AI application in Indian healthcare is discussed. This article then captures the range of AI applications in healthcare in India. The AI applications range from those used in early screening or diagnostic space, to those used in treatment and rehabilitation. In the Indian healthcare space innovations that can improve rural healthcare is greatly valued. Several of the start ups featured in this article have sought to apply AI to rural Indian healthcare to address the gaps. With smartphone boom AI enabled reality can be possible. However there are several challenges to scale up use of AI in healthcare delivery in India about which this article concludes with. Currently most of the applications are still at a regional level. Several issues are there to scale up the data level needs to be addressed before AI can truly be a reality for India. Data availability, data pooling, data collection, data sharing, data protection, data privacy are among the multifaceted issued which must be sorted out. Other challenges range from human resource issues to lack of awareness to need to address ethical issues in AI based innovations, to cyber security issues, lack of infrastructure, besides the high cost of investing in AI based innovations. Several policy mechanisms and regulatory frameworks are being brought out to address these challenges via NITI Aayog Towards Responsible #AIforAll. The article concludes on the fact that AI in healthcare can potentially change the landscape if done right.

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Section: Ai In Screeningmentioning

confidence: 99%

Use of artificial intelligence in healthcare delivery in India

Pradhan¹,

John²,

Sandhu³

2021

J Hosp Manag Health Policy

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“…The author in [20] has shown an important aim, which is to provide a comprehensive review of the current state of edge computing with the use of smart end devices. In addition, the author has presented an overview of applications where deep learning technology is used at the network edge, discussing different methodologies for quickly executing deep learning inference across a combination of end devices, edge servers, and the cloud, and describing methods for training deep learning models across multiple edge devices [21]. In [22], the author mentioned the risk methodology for the medical information system.…”

Section: Related Workmentioning

confidence: 99%

A Highly Effective Route for Real-Time Traffic Using an IoT Smart Algorithm for Tele-Surgery Using 5G Networks

Abujassar

Yaseen

Al-Adwan

2021

JSAN

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Nowadays, networks use many different paths to exchange data. However, our research will construct a reliable path in the networks among a huge number of nodes for use in tele-surgery using medical applications such as healthcare tracking applications, including tele-surgery which lead to optimizing medical quality of service (m-QoS) during the COVID-19 situation. Many people could not travel due to the current issues, for fear of spreading the covid-19 virus. Therefore, our paper will provide a very trusted and reliable method of communication between a doctor and his patient so that the latter can do his operation even from a far distance. The communication between the doctor and his/her patient will be monitored by our proposed algorithm to make sure that the data will be received without delay. We test how we can invest buffer space that can be used efficiently to reduce delays between source and destination, avoiding loss of high-priority data packets. The results are presented in three stages. First, we show how to obtain the greatest possible reduction in rate variability when the surgeon begins an operation using live streaming. Second, the proposed algorithm reduces congestion on the determined path used for the online surgery. Third, we have evaluated the affection of optimal smoothing algorithm on the network parameters such as peak-to-mean ratio and delay to optimize m-QoS. We propose a new Smart-Rout Control algorithm (s-RCA) for creating a virtual smart path between source and destination to transfer the required data traffic between them, considering the number of hops and link delay. This provides a reliable connection that can be used in healthcare surgery to guarantee that all instructions are received without any delay, to be executed instantly. This idea can improve m-QoS in distance surgery, with trusted paths. The new s-RCA can be adapted with an existing routing protocol to track the primary path and monitor emergency packets received in node buffers, for direct forwarding via the demand path, with extended features.

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“…Reliable data communication plays a vital role in IoT for reliable data fusion, data mining, context-aware based services, and user privacy [29]. A way of addressing these concerns is to theoretically virtualize the IoT environment across the cloud, which is known as the Cloud-of-Things (CoT), and then connect each device with one or more cloud agents [6,30] that have developed a CoTAG (CoT agent grouping), algorithm to shape agent groups based on the reliability details and credibility obtained by agents. They carry out the tests in a simulated scenario to check this algorithm's reliability and efficacy.…”

Section: Background and Related Workmentioning

confidence: 99%

“…As these devices are continuously connected to the internet, they can detect abnormalities, and provide emergency services simultaneously [5]. Healthcare covers various topics, including medical healthcare, diagnostic assessment, and cure health awareness among people [6]. In developing countries, it is still a big challenge to monitor chronic patients in real-time environments due to the poor adaption of technology.…”

Section: Introductionmentioning

confidence: 99%

Security Framework for IoT Based Real-Time Health Applications

et al. 2021

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The amazing fusion of the internet of things (IoT) into traditional health monitoring systems has produced remarkable advances in the field of e-health. Different wireless body area network devices and sensors are providing real-time health monitoring services. As the number of IoT devices is rapidly booming, technological and security challenges are also rising day by day. The data generated from sensor-based devices need confidentiality, integrity, authenticity, and end-to-end security for safe communication over the public network. IoT-based health monitoring systems work in a layered manner, comprising a perception layer, a network layer, and an application layer. Each layer has some security, and privacy concerns that need to be addressed accordingly. A lot of research has been conducted to resolve these security issues in different domains of IoT. Several frameworks for the security of IoT-based e-health systems have also been developed. This paper introduces a security framework for real-time health monitoring systems to ensure data confidentiality, integrity, and authenticity by using two common IoT protocols, namely constrained application protocol (CoAP) and message query telemetry transports (MQTT). This security framework aims to defend sensor data against the security loopholes while it is continuously transmitting over the layers and uses hypertext transfer protocols (HTTPs) for this purpose. As a result, it shields from the breach with a very low ratio of risk. The methodology of this paper focuses on how the security framework of IoT-based real-time health systems is protected under the tiers of CoAP and HTTPs. CoAP works alongside HTTPs and is responsible for providing end-to-end security solutions.

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A Secure Framework for IoT-Based Healthcare System

Cited by 15 publications

References 13 publications

Use of artificial intelligence in healthcare delivery in India

Use of artificial intelligence in healthcare delivery in India

A Highly Effective Route for Real-Time Traffic Using an IoT Smart Algorithm for Tele-Surgery Using 5G Networks

Security Framework for IoT Based Real-Time Health Applications

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