Local-Global-Graph Network-Based Biokey Generation with Electrocardiogram Signal and Lightweight Authentication in Cloud-Based Internet of Medical Things Networks

The internet of medical things (IoMT) is regarded as a promising framework, which is used to expand and improve telemedicine services. Cloud-based IoMT refers to the integration of medical devices and sensors with cloud computing infrastructure, enabling real-time remote data collection, processing, storage, and analysis. This architecture supports the efficient management of patient health information and facilitates advanced telemedicine services by offering scalable, secure, and accessible healthcare solutions. Ensuring secure access and communication in such systems is critical, as vulnerabilities in the network can expose sensitive patient data to significant risks. Among various security measures, authentication using biomedical signals, particularly electrocardiogram (ECG) signals, is gaining attention due to their unique, individual-specific characteristics. Therefore, this paper develops a new approach called local-global-graph network-based biokey generation (LGGNet-BioKey) for authentication in Cloud-based IoMT. Initially, the Cloud-based IoMT network is simulated, and it includes three entities, like cloud server, gateway, and patient. First, the public key and security parameters are initialized, and then the entities are registered with the cloud server. Next, the key generation is done using LGGNet, and then the BioKey generation is performed using an ECG signal. Next, the lightweight authentication is done and lastly, attribute-based encryption and decryption are performed in the data preservation phase. Furthermore, the LGGNet-BioKey model measured an execution time, memory usage, and key generation time of 3.772 sec, 9.096 MB, and 3.771 sec.

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Publication Details

Journal
Critical Reviews in Biomedical Engineering
Published
2025-12-11
DOI
https://doi.org/10.1615/critrevbiomedeng.2025058925
Primary Topic
Wireless Body Area Networks
Type
article
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article

Local-Global-Graph Network-Based Biokey Generation with Electrocardiogram Signal and Lightweight Authentication in Cloud-Based Internet of Medical Things Networks

Sanjeev Kumar A N, Ramesh Naik B
Critical Reviews in Biomedical Engineering
Wireless Body Area Networks
article

Local-Global-Graph Network-Based Biokey Generation with Electrocardiogram Signal and Lightweight Authentication in Cloud-Based Internet of Medical Things Networks

Sanjeev Kumar A N, Ramesh Naik B
article en

Abstract

The internet of medical things (IoMT) is regarded as a promising framework, which is used to expand and improve telemedicine services. Cloud-based IoMT refers to the integration of medical devices and sensors with cloud computing infrastructure, enabling real-time remote data collection, processing, storage, and analysis. This architecture supports the efficient management of patient health information and facilitates advanced telemedicine services by offering scalable, secure, and accessible healthcare solutions. Ensuring secure access and communication in such systems is critical, as vulnerabilities in the network can expose sensitive patient data to significant risks. Among various security measures, authentication using biomedical signals, particularly electrocardiogram (ECG) signals, is gaining attention due to their unique, individual-specific characteristics. Therefore, this paper develops a new approach called local-global-graph network-based biokey generation (LGGNet-BioKey) for authentication in Cloud-based IoMT. Initially, the Cloud-based IoMT network is simulated, and it includes three entities, like cloud server, gateway, and patient. First, the public key and security parameters are initialized, and then the entities are registered with the cloud server. Next, the key generation is done using LGGNet, and then the BioKey generation is performed using an ECG signal. Next, the lightweight authentication is done and lastly, attribute-based encryption and decryption are performed in the data preservation phase. Furthermore, the LGGNet-BioKey model measured an execution time, memory usage, and key generation time of 3.772 sec, 9.096 MB, and 3.771 sec.

Critical Reviews in Biomedical EngineeringVol. 54(1)
GITAM University (IN)
Openalex Percentile: Top 61%
Wireless Body Area Networks
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Local-Global-Graph Network-Based Biokey Generation with Electrocardiogram Signal and Lightweight Authentication in Cloud-Based Internet of Medical Things Networks — Sanjeev Kumar A N, Ramesh Naik B · Critical Reviews in Biomedical Engineering (2025) | TGRS Research Map | TGRS