Role of the Internet of Things and deep learning for the growth of healthcare technology

Bhatia, Dinesh; Bagyaraj, S.; Karthick, S.; Mishra, Alok; Malviya, Amit

doi:10.1016/b978-0-12-822226-3.00005-2

Cited by 3 publications

References 8 publications

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Amalgamation of Blockchain Technology and Internet of Things for Healthcare Applications

Bhatia

Mishra

Mukherjee

2021

Blockchain for 5g-Enabled IoT

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The integration of blockchain and the Internet of Things (IoT) helps to strengthen and leverage mutual advantages in a variety of industrial domains including healthcare. The healthcare industry is one of the largest and fastest-growing industries involving more than 10% of the gross domestic product (GDP) of several countries globally. The use of blockchain in IoT can help to track multiple devices in the network, avoid duplication of malicious data entries, disallow data tampering, and provide enhanced security and privacy. Several devices are connected in an IoT network for fast-paced 5G-enabled data transfer environment for different industrial applications for collecting information and processing it, and the chances of failure of this centralized system are much higher. The time required to retrieve data from different devices, existing protocols, and access control mechanism employed presently may not work in the future as they are centralized based mechanisms [1,2]. The deployment of blockchain in IoT allows distributed, decentralized ledger records with high security, privacy, improved efficiency, and authenticity of data [1,3,4].Soon, the blockchain technology would immensely benefit and revolutionize the healthcare sector by ensuring data transparency, reducing costs of service delivery,

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Amalgamation of Blockchain Technology and Internet of Things for Healthcare Applications

Bhatia

Mishra

Mukherjee

2021

Blockchain for 5g-Enabled IoT

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Technology as a Catalyst for Medical Tourism

Jani,

Chaudhary,

Saini

2024

Medical Tourism in Developing Countries

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Internet of Things Security Early Warning Model Based on Deep Learning in Edge Computing Environment

Zhong,

Lv,

et al. 2024

J CIRCUIT SYST COMP

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Aiming at the problems of poor real-time processing and low security performance caused by the massive information of the Internet of things, a security early warning model of the Internet of things based on deep learning in edge computing environment is proposed. Firstly, the system architecture of the Internet of things is designed by using the edge computing technology, in which the intelligent router is used to obtain the network stub and send it to the nearest edge computing node for anomaly detection. Then, the attention mechanism is used to improve the long short-term memory network (LSTM), and the multidimensional LSTM model is constructed. At the same time, it is used to analyze the combined network data. Finally, according to the set threshold value, judge whether there is abnormal behavior in the network, and give early warning in time to take security defense measures. The experimental analysis of the proposed model based on NS2 simulation platform shows that its early warning success rate and time are 95.2% and 20.6[Formula: see text]ms, respectively, and it can detect and defend various network attacks well, with high security performance.

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Role of the Internet of Things and deep learning for the growth of healthcare technology

Cited by 3 publications

References 8 publications

Amalgamation of Blockchain Technology and Internet of Things for Healthcare Applications

Amalgamation of Blockchain Technology and Internet of Things for Healthcare Applications

Technology as a Catalyst for Medical Tourism

Internet of Things Security Early Warning Model Based on Deep Learning in Edge Computing Environment

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