[HTML][HTML] Model aggregation techniques in federated learning: A comprehensive survey
Federated learning (FL) is a distributed machine learning (ML) approach that enables
models to be trained on client devices while ensuring the privacy of user data. Model …
models to be trained on client devices while ensuring the privacy of user data. Model …
A review of secure federated learning: privacy leakage threats, protection technologies, challenges and future directions
L Ge, H Li, X Wang, Z Wang - Neurocomputing, 2023 - Elsevier
Advances in the new generation of Internet of Things (IoT) technology are propelling the
growth of intelligent industrial applications worldwide. Simultaneously, widespread adoption …
growth of intelligent industrial applications worldwide. Simultaneously, widespread adoption …
Distance-aware hierarchical federated learning in blockchain-enabled edge computing network
Federated learning (FL) has been proposed as an emerging paradigm to perform privacy-
preserving distributed machine learning in the Internet of Things (IoT). However, the …
preserving distributed machine learning in the Internet of Things (IoT). However, the …
Federated learning using game strategies: State-of-the-art and future trends
R Gupta, J Gupta - Computer Networks, 2023 - Elsevier
Federated learning (FL) is a new and promising paradigm that allows devices to learn
without sharing data with the centralized server. It is often built on decentralized data where …
without sharing data with the centralized server. It is often built on decentralized data where …
Trustworthy federated learning: A survey
Federated Learning (FL) has emerged as a significant advancement in the field of Artificial
Intelligence (AI), enabling collaborative model training across distributed devices while …
Intelligence (AI), enabling collaborative model training across distributed devices while …
[HTML][HTML] A decentralized data evaluation framework in federated learning
Federated Learning (FL) is a type of distributed deep learning framework in which multiple
devices train a local model using local data, and the gradients of the local model are then …
devices train a local model using local data, and the gradients of the local model are then …
Blockchain empowered federated learning ecosystem for securing consumer IoT features analysis
A Alghamdi, J Zhu, G Yin, M Shorfuzzaman… - Sensors, 2022 - mdpi.com
Resource constraint Consumer Internet of Things (CIoT) is controlled through gateway
devices (eg, smartphones, computers, etc.) that are connected to Mobile Edge Computing …
devices (eg, smartphones, computers, etc.) that are connected to Mobile Edge Computing …
Secure and scalable blockchain-based federated learning for cryptocurrency fraud detection: A systematic review
With the wide adoption of cryptocurrency, blockchain technologies have become the
foundation of such digital currencies. However, this adoption has been accompanied by a …
foundation of such digital currencies. However, this adoption has been accompanied by a …
Trustworthy federated learning: a comprehensive review, architecture, key challenges, and future research prospects
Federated Learning (FL) emerged as a significant advancement in the field of Artificial
Intelligence (AI), enabling collaborative model training across distributed devices while …
Intelligence (AI), enabling collaborative model training across distributed devices while …
FedGST: An efficient federated graph neural network for spatio-temporal PoI recommendation
With the proliferation of sensor networks in urban areas, vast amounts of data from location-
based social network platforms are now available, thus enabling the stakeholders to …
based social network platforms are now available, thus enabling the stakeholders to …