Decentralized federated learning: Fundamentals, state of the art, frameworks, trends, and challenges

ETM Beltrán, MQ Pérez, PMS Sánchez… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
In recent years, Federated Learning (FL) has gained relevance in training collaborative
models without sharing sensitive data. Since its birth, Centralized FL (CFL) has been the …

Blockchain-empowered federated learning: Challenges, solutions, and future directions

J Zhu, J Cao, D Saxena, S Jiang, H Ferradi - ACM Computing Surveys, 2023 - dl.acm.org
Federated learning is a privacy-preserving machine learning technique that trains models
across multiple devices holding local data samples without exchanging them. There are …

Combining federated learning and edge computing toward ubiquitous intelligence in 6G network: Challenges, recent advances, and future directions

Q Duan, J Huang, S Hu, R Deng… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
Full leverage of the huge volume of data generated on a large number of user devices for
providing intelligent services in the 6G network calls for Ubiquitous Intelligence (UI). A key to …

Blockchain meets federated learning in healthcare: A systematic review with challenges and opportunities

R Myrzashova, SH Alsamhi… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
Recently, innovations in the Internet of Medical Things (IoMT), information and
communication technologies, and machine learning (ML) have enabled smart healthcare …

STSIR: An individual-group game-based model for disclosing virus spread in Social Internet of Things

G Wu, L Xie, H Zhang, J Wang, S Shen, S Yu - Journal of Network and …, 2023 - Elsevier
Abstract Social Internet of Things (SIoT) with deep integration of Internet of Things and social
networks has become a target of a large number of hackers who attempt to spread viruses …

Decentralized federated learning: A survey and perspective

L Yuan, Z Wang, L Sun, SY Philip… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Federated learning (FL) has been gaining attention for its ability to share knowledge while
maintaining user data, protecting privacy, increasing learning efficiency, and reducing …

A review of privacy enhancement methods for federated learning in healthcare systems

X Gu, F Sabrina, Z Fan, S Sohail - International Journal of Environmental …, 2023 - mdpi.com
Federated learning (FL) provides a distributed machine learning system that enables
participants to train using local data to create a shared model by eliminating the requirement …

A survey on decentralized federated learning

E Gabrielli, G Pica, G Tolomei - arXiv preprint arXiv:2308.04604, 2023 - arxiv.org
In recent years, federated learning (FL) has become a very popular paradigm for training
distributed, large-scale, and privacy-preserving machine learning (ML) systems. In contrast …

PPFchain: A novel framework privacy-preserving blockchain-based federated learning method for sensor networks

BB Sezer, H Turkmen, U Nuriyev - Internet of Things, 2023 - Elsevier
Abstract Internet of Things (IoT) has been widely used in many smart applications such as
smart cities, smart agriculture, healthcare, industry, etc. In addition, the importance of IoT …

Blockchain-oriented privacy protection of sensitive data in the internet of vehicles

C Xu, H Wu, H Liu, W Gu, Y Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The Internet of Vehicles is the specific instantiation of the Internet of Things in the field of
transportation. Vehicle and driving data are often used to mine information about people's …