Privacy-Preserving AI Framework for 6G-Enabled Consumer Electronics
In the realm of consumer electronics for 6G communication, AI has emerged as a significant
player. However, the proliferation of devices at the edge of network causes the generation of …
player. However, the proliferation of devices at the edge of network causes the generation of …
Privacy-preserving blockchain-enabled federated learning for B5G-Driven edge computing
The arrival of the fifth-generation technology standard for broadband cellular networks (5G)
and beyond 5G networks (B5G) rises the speed and robustness ceiling of communicating …
and beyond 5G networks (B5G) rises the speed and robustness ceiling of communicating …
A secure federated learning framework for 5G networks
Federated learning (FL) has recently been proposed as an emerging paradigm to build
machine learning models using distributed training datasets that are locally stored and …
machine learning models using distributed training datasets that are locally stored and …
Privacy-preserving asynchronous grouped federated learning for IoT
Federated learning (FL), a cooperative distributed learning framework, has been employed
in various intelligent Internet of Things (IoT) applications (eg, smart health-care, smart home …
in various intelligent Internet of Things (IoT) applications (eg, smart health-care, smart home …
A Novel Federated Learning Framework Based on Conditional Generative Adversarial Networks for Privacy Preserving in 6G
J Huang, Z Chen, S Liu, H Long - Electronics, 2024 - mdpi.com
With the rapid development of 6G networks, data transmission speed has significantly
increased, making data privacy protection issues even more crucial. The federated learning …
increased, making data privacy protection issues even more crucial. The federated learning …
Secure Aggregation in Heterogeneous Federated Learning for Digital Ecosystems
Privacy-preserving federated learning (PPFL) is vital for Industry 5.0 digital ecosystems due
to the increasing number of interconnected devices and the volume of shared sensitive data …
to the increasing number of interconnected devices and the volume of shared sensitive data …
RR-LADP: A privacy-enhanced federated learning scheme for internet of everything
While the widespread use of ubiquitously connected devices in Internet of Everything (IoE)
offers enormous benefits, it also raises serious privacy concerns. Federated learning, as one …
offers enormous benefits, it also raises serious privacy concerns. Federated learning, as one …
Efficient privacy-preserving federated learning for resource-constrained edge devices
A large volume of data is generated by ubiquitous Internet-of-Things (IoT) devices and
utilized to train machine learning models by IoT manufacturers to provide users with better …
utilized to train machine learning models by IoT manufacturers to provide users with better …
[HTML][HTML] Federated learning for 6G-enabled secure communication systems: a comprehensive survey
Abstract Machine learning (ML) and Deep learning (DL) models are popular in many areas,
from business, medicine, industries, healthcare, transportation, smart cities, and many more …
from business, medicine, industries, healthcare, transportation, smart cities, and many more …
[Retracted] AFLPC: An Asynchronous Federated Learning Privacy‐Preserving Computing Model Applied to 5G‐V2X
J Huang, C Xu, Z Ji, S Xiao, T Liu… - Security and …, 2022 - Wiley Online Library
Federated learning can effectively protect local data privacy in 5G‐V2X environment and
ensure data protection in Internet of vehicles environment. The advantages of low delay of …
ensure data protection in Internet of vehicles environment. The advantages of low delay of …