Security and privacy on 6g network edge: A survey

B Mao, J Liu, Y Wu, N Kato - IEEE communications surveys & …, 2023 - ieeexplore.ieee.org
To meet the stringent service requirements of 6G applications such as immersive cloud
eXtended Reality (XR), holographic communication, and digital twin, there is no doubt that …

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 …

Federated learning for internet of things: A comprehensive survey

DC Nguyen, M Ding, PN Pathirana… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
The Internet of Things (IoT) is penetrating many facets of our daily life with the proliferation of
intelligent services and applications empowered by artificial intelligence (AI). Traditionally …

A survey on federated learning for resource-constrained IoT devices

A Imteaj, U Thakker, S Wang, J Li… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Federated learning (FL) is a distributed machine learning strategy that generates a global
model by learning from multiple decentralized edge clients. FL enables on-device training …

Federated learning for internet of things: Recent advances, taxonomy, and open challenges

LU Khan, W Saad, Z Han, E Hossain… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
The Internet of Things (IoT) will be ripe for the deployment of novel machine learning
algorithm for both network and application management. However, given the presence of …

[HTML][HTML] Asynchronous federated learning on heterogeneous devices: A survey

C Xu, Y Qu, Y Xiang, L Gao - Computer Science Review, 2023 - Elsevier
Federated learning (FL) is a kind of distributed machine learning framework, where the
global model is generated on the centralized aggregation server based on the parameters of …

Federated learning-based AI approaches in smart healthcare: concepts, taxonomies, challenges and open issues

A Rahman, MS Hossain, G Muhammad, D Kundu… - Cluster computing, 2023 - Springer
Abstract Federated Learning (FL), Artificial Intelligence (AI), and Explainable Artificial
Intelligence (XAI) are the most trending and exciting technology in the intelligent healthcare …

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 …

Blockchain empowered asynchronous federated learning for secure data sharing in internet of vehicles

Y Lu, X Huang, K Zhang, S Maharjan… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In Internet of Vehicles (IoV), data sharing among vehicles for collaborative analysis can
improve the driving experience and service quality. However, the bandwidth, security and …

A survey of recent advances in edge-computing-powered artificial intelligence of things

Z Chang, S Liu, X Xiong, Z Cai… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
The Internet of Things (IoT) has created a ubiquitously connected world powered by a
multitude of wired and wireless sensors generating a variety of heterogeneous data over …