[HTML][HTML] A survey on federated learning: challenges and applications
J Wen, Z Zhang, Y Lan, Z Cui, J Cai… - International Journal of …, 2023 - Springer
Federated learning (FL) is a secure distributed machine learning paradigm that addresses
the issue of data silos in building a joint model. Its unique distributed training mode and the …
the issue of data silos in building a joint model. Its unique distributed training mode and the …
Federated learning for privacy preservation in smart healthcare systems: A comprehensive survey
Recent advances in electronic devices and communication infrastructure have
revolutionized the traditional healthcare system into a smart healthcare system by using …
revolutionized the traditional healthcare system into a smart healthcare system by using …
Federated deep learning for cyber security in the internet of things: Concepts, applications, and experimental analysis
In this article, we present a comprehensive study with an experimental analysis of federated
deep learning approaches for cyber security in the Internet of Things (IoT) applications …
deep learning approaches for cyber security in the Internet of Things (IoT) applications …
Integration of federated machine learning and blockchain for the provision of secure big data analytics for Internet of Things
Big data enables the optimization of complex supply chains through Machine Learning (ML)-
based data analytics. However, data analytics comes with challenges such as the loss of …
based data analytics. However, data analytics comes with challenges such as the loss of …
A comprehensive review on deep learning algorithms: Security and privacy issues
Abstract Machine Learning (ML) algorithms are used to train the machines to perform
various complicated tasks that begin to modify and improve with experiences. It has become …
various complicated tasks that begin to modify and improve with experiences. It has become …
[HTML][HTML] Gradient boosting for health IoT federated learning
Federated learning preserves the privacy of user data through Machine Learning (ML). It
enables the training of an ML model during this process. The Healthcare Internet of Things …
enables the training of an ML model during this process. The Healthcare Internet of Things …
Poisoning attacks in federated learning: A survey
G Xia, J Chen, C Yu, J Ma - IEEE Access, 2023 - ieeexplore.ieee.org
Federated learning faces many security and privacy issues. Among them, poisoning attacks
can significantly impact global models, and malicious attackers can prevent global models …
can significantly impact global models, and malicious attackers can prevent global models …
RobustFL: Robust federated learning against poisoning attacks in industrial IoT systems
Industrial Internet of Things (IIoT) systems are key enabling infrastructures that sustain the
functioning of production and manufacturing. To satisfy the intelligence demands, federated …
functioning of production and manufacturing. To satisfy the intelligence demands, federated …
BFG: privacy protection framework for internet of medical things based on blockchain and federated learning
W Liu, Y He, X Wang, Z Duan, W Liang… - Connection Science, 2023 - Taylor & Francis
The deep integration of Internet of Medical Things (IoMT) and Artificial intelligence makes
the further development of intelligent medical services possible, but privacy leakage and …
the further development of intelligent medical services possible, but privacy leakage and …