Edge learning for 6g-enabled internet of things: A comprehensive survey of vulnerabilities, datasets, and defenses
The deployment of the fifth-generation (5G) wireless networks in Internet of Everything (IoE)
applications and future networks (eg, sixth-generation (6G) networks) has raised a number …
applications and future networks (eg, sixth-generation (6G) networks) has raised a number …
Blockchain-based two-stage federated learning with non-IID data in IoMT system
The Internet of Medical Things (IoMT) has a bright future with the development of smart
mobile devices. Information technology is also leading changes in the healthcare industry …
mobile devices. Information technology is also leading changes in the healthcare industry …
A privacy-preserving social computing framework for health management using federated learning
Currently, health management driven by intelligent means is a general demand of social
systems. Although a number of researchers have paid attention to such areas, they have …
systems. Although a number of researchers have paid attention to such areas, they have …
A comprehensive review on Federated Learning for Data-Sensitive Application: Open issues & challenges
Abstract Artificial intelligence employs Machine Learning (ML) and Deep Learning (DL) to
analyze data. In both, the data is stored centrally. The data involved may be sensitive and …
analyze data. In both, the data is stored centrally. The data involved may be sensitive and …
[HTML][HTML] Federated learning for the internet-of-medical-things: A survey
VK Prasad, P Bhattacharya, D Maru, S Tanwar… - Mathematics, 2022 - mdpi.com
Recently, in healthcare organizations, real-time data have been collected from connected or
implantable sensors, layered protocol stacks, lightweight communication frameworks, and …
implantable sensors, layered protocol stacks, lightweight communication frameworks, and …
Fedcare: Federated learning for resource-constrained healthcare devices in iomt system
In social IoMT systems, resource-constrained devices face the challenges of limited
computation, bandwidth, and privacy in the deployment of deep learning models. Federated …
computation, bandwidth, and privacy in the deployment of deep learning models. Federated …
UDSem: A unified distributed learning framework for semantic communications over wireless networks
End-to-end semantic communications (ESC) rely on deep neural networks (DNN) to boost
the communication efficiency by only transmitting the semantics of data. However, ESC is …
the communication efficiency by only transmitting the semantics of data. However, ESC is …
Feel: Federated learning framework for elderly healthcare using edge-iomt
Recent advancements in artificial intelligence (AI) and IoT technology have revolutionized
the healthcare industry by providing effective remote healthcare. Furthermore, with the aging …
the healthcare industry by providing effective remote healthcare. Furthermore, with the aging …
Semisupervised Federated Learning for Temporal News Hyperpatism Detection
U Ahmed, JCW Lin, G Srivastava - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The proliferation of false and erroneous information on the Internet has posed a challenge to
the accurate exchange of information. To address this issue, a semisupervised system …
the accurate exchange of information. To address this issue, a semisupervised system …
A privacy-preserved IoMT-based mental stress detection framework with federated learning
Abstract Internet of Medical Things (IoMT) can be leveraged for periodic sensing and
recording of different health parameters using sensors, wireless communications, and …
recording of different health parameters using sensors, wireless communications, and …