A federated bidirectional connection broad learning scheme for secure data sharing in Internet of Vehicles

X Yuan, J Chen, N Zhang, X Fang… - China …, 2021 - ieeexplore.ieee.org
Data sharing in Internet of Vehicles (IoV) makes it possible to provide personalized services
for users by service providers in Intelligent Transportation Systems (ITS). As IoV is a multi …

Blockchain-based decentralized model aggregation for cross-silo federated learning in industry 4.0

T Ranathunga, A McGibney, S Rea… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
Traditional federated learning (FL) adopts a client-server architecture where FL clients (eg,
IoT edge devices) train a common global model with the help of a centralized orchestrator …

Decentralized federated learning based on blockchain: concepts, framework, and challenges

H Zhang, S Jiang, S Xuan - Computer Communications, 2024 - Elsevier
Decentralized federated learning integrates advanced technologies, including distributed
computing and secure encryption methodologies, to facilitate a robust and efficient …

Decentralized deep learning for multi-access edge computing: A survey on communication efficiency and trustworthiness

Y Sun, H Ochiai, H Esaki - IEEE Transactions on Artificial …, 2021 - ieeexplore.ieee.org
Wider coverage and a better solution to a latency reduction in 5G necessitate its
combination with multi-access edge computing technology. Decentralized deep learning …

Reputation-aware hedonic coalition formation for efficient serverless hierarchical federated learning

JS Ng, WYB Lim, Z Xiong, X Cao, J Jin… - … on Parallel and …, 2021 - ieeexplore.ieee.org
Amid growing concerns on data privacy, Federated Learning (FL) has emerged as a
promising privacy preserving distributed machine learning paradigm. Given that the FL …

Applying federated learning in software-defined networks: A survey

X Ma, L Liao, Z Li, RX Lai, M Zhang - Symmetry, 2022 - mdpi.com
Federated learning (FL) is a type of distributed machine learning approacs that trains global
models through the collaboration of participants. It protects data privacy as participants only …

Asynchronous federated learning system based on permissioned blockchains

R Wang, WT Tsai - Sensors, 2022 - mdpi.com
The existing federated learning framework is based on the centralized model coordinator,
which still faces serious security challenges such as device differentiated computing power …

A secure and privacy preserved infrastructure for VANETs based on federated learning with local differential privacy

H Batool, A Anjum, A Khan, S Izzo, C Mazzocca… - Information …, 2024 - Elsevier
Advancements in Vehicular ad-hoc Network (VANET) technology have led to a growing
network of interconnected devices, including edge devices, resulting in substantial data …

[HTML][HTML] FedHEONN: Federated and homomorphically encrypted learning method for one-layer neural networks

O Fontenla-Romero, B Guijarro-Berdiñas… - Future Generation …, 2023 - Elsevier
Federated learning (FL) is a distributed approach to developing collaborative learning
models from decentralized data. This is relevant to many real applications, such as in the …

Fuzzy consensus with federated learning method in medical systems

D Połap - IEEE Access, 2021 - ieeexplore.ieee.org
Large-scale group decision-making (LSGDM) is one of the main open problems where a
decision is made by many different results. Moreover, there is also a problem with how to …