Heterogeneous federated learning: State-of-the-art and research challenges

M Ye, X Fang, B Du, PC Yuen, D Tao - ACM Computing Surveys, 2023 - dl.acm.org
Federated learning (FL) has drawn increasing attention owing to its potential use in large-
scale industrial applications. Existing FL works mainly focus on model homogeneous …

A comprehensive survey of privacy-preserving federated learning: A taxonomy, review, and future directions

X Yin, Y Zhu, J Hu - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
The past four years have witnessed the rapid development of federated learning (FL).
However, new privacy concerns have also emerged during the aggregation of the …

Survey on federated learning threats: Concepts, taxonomy on attacks and defences, experimental study and challenges

N Rodríguez-Barroso, D Jiménez-López, MV Luzón… - Information …, 2023 - Elsevier
Federated learning is a machine learning paradigm that emerges as a solution to the privacy-
preservation demands in artificial intelligence. As machine learning, federated learning is …

Federated learning in smart cities: Privacy and security survey

R Al-Huthaifi, T Li, W Huang, J Gu, C Li - Information Sciences, 2023 - Elsevier
Over the last decade, smart cities (SC) have been developed worldwide. Implementing big
data and the internet of things improves the monitoring and integration of different …

Homomorphic encryption-based privacy-preserving federated learning in IoT-enabled healthcare system

L Zhang, J Xu, P Vijayakumar… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In this work, the federated learning mechanism is introduced into the deep learning of
medical models in Internet of Things (IoT)-based healthcare system. Cryptographic …

Secure and provenance enhanced internet of health things framework: A blockchain managed federated learning approach

MA Rahman, MS Hossain, MS Islam, NA Alrajeh… - Ieee …, 2020 - ieeexplore.ieee.org
Recent advancements in the Internet of Health Things (IoHT) have ushered in the wide
adoption of IoT devices in our daily health management. For IoHT data to be acceptable by …

Privacy-preserving aggregation in federated learning: A survey

Z Liu, J Guo, W Yang, J Fan, KY Lam… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Over the recent years, with the increasing adoption of Federated Learning (FL) algorithms
and growing concerns over personal data privacy, Privacy-Preserving Federated Learning …

Securing federated learning with blockchain: a systematic literature review

A Qammar, A Karim, H Ning, J Ding - Artificial Intelligence Review, 2023 - Springer
Federated learning (FL) is a promising framework for distributed machine learning that trains
models without sharing local data while protecting privacy. FL exploits the concept of …

pfl-bench: A comprehensive benchmark for personalized federated learning

D Chen, D Gao, W Kuang, Y Li… - Advances in Neural …, 2022 - proceedings.neurips.cc
Abstract Personalized Federated Learning (pFL), which utilizes and deploys distinct local
models, has gained increasing attention in recent years due to its success in handling the …

Federatedscope: A flexible federated learning platform for heterogeneity

Y Xie, Z Wang, D Gao, D Chen, L Yao, W Kuang… - arXiv preprint arXiv …, 2022 - arxiv.org
Although remarkable progress has been made by existing federated learning (FL) platforms
to provide infrastructures for development, these platforms may not well tackle the …