Combining federated learning and edge computing toward ubiquitous intelligence in 6G network: Challenges, recent advances, and future directions
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 …
providing intelligent services in the 6G network calls for Ubiquitous Intelligence (UI). A key to …
Blockchain assisted decentralized federated learning (BLADE-FL): Performance analysis and resource allocation
Federated learning (FL), as a distributed machine learning paradigm, promotes personal
privacy by local data processing at each client. However, relying on a centralized server for …
privacy by local data processing at each client. However, relying on a centralized server for …
FLEAM: A federated learning empowered architecture to mitigate DDoS in industrial IoT
Due to resource constraints and working surroundings, many IIoT nodes are easily hacked
and turn into zombies from which to launch attacks. It is challenging to detect such …
and turn into zombies from which to launch attacks. It is challenging to detect such …
Lightweight blockchain-empowered secure and efficient federated edge learning
Federated Learning (FL) has emerged as a privacy-preserving distributed Machine Learning
paradigm, which collaboratively trains a shared global model across a number of end …
paradigm, which collaboratively trains a shared global model across a number of end …
Federated and asynchronized learning for autonomous and intelligent things
The Internet of Things (IoT) intertwined with autonomous and intelligent things (AITs) is
beginning to affect many aspects of our daily lives. Along with this trend, asynchronous …
beginning to affect many aspects of our daily lives. Along with this trend, asynchronous …
Intruder detection in VANET data streams using federated learning for smart city environments
Vehicular networks improve quality of life, security, and safety, making them crucial to smart
city development. With the rapid advancement of intelligent vehicles, the confidentiality and …
city development. With the rapid advancement of intelligent vehicles, the confidentiality and …
PervasiveFL: Pervasive federated learning for heterogeneous IoT systems
Federated learning (FL) has been recognized as a promising collaborative on-device
machine learning method in the design of Internet of Things (IoT) systems. However, most …
machine learning method in the design of Internet of Things (IoT) systems. However, most …
FedCross: Towards accurate federated learning via multi-model cross-aggregation
As a promising distributed machine learning paradigm, Federated Learning (FL) has
attracted increasing attention to deal with data silo problems without compromising user …
attracted increasing attention to deal with data silo problems without compromising user …
FedCR: Personalized federated learning based on across-client common representation with conditional mutual information regularization
In personalized federated learning (PFL), multiple clients train customized models to fulfill
their personal objectives, which, however, are prone to overfitting to local data due to the …
their personal objectives, which, however, are prone to overfitting to local data due to the …
Fedsac: Dynamic submodel allocation for collaborative fairness in federated learning
Collaborative fairness stands as an essential element in federated learning to encourage
client participation by equitably distributing rewards based on individual contributions …
client participation by equitably distributing rewards based on individual contributions …