ASR-Fed: agnostic straggler-resilient semi-asynchronous federated learning technique for secured drone network
Federated Learning (FL) has emerged as a transformative artificial intelligence paradigm,
facilitating knowledge sharing among distributed edge devices while upholding data …
facilitating knowledge sharing among distributed edge devices while upholding data …
Radio Frequency Fingerprint Identification of WiFi Signals Based on Federated Learning for Different Data Distribution Scenarios
The number of terminal devices has skyrocketed along with the quick growth of cognitive
radio networks. Massive equipment produce a lot of data that should not be shared, often …
radio networks. Massive equipment produce a lot of data that should not be shared, often …
Unmanned Vehicles in 6G Networks: A Unifying Treatment of Problems, Formulations, and Tools
W Hurst, S Evmorfos, A Petropulu, Y Mostofi - arXiv preprint arXiv …, 2024 - arxiv.org
Unmanned Vehicles (UVs) functioning as autonomous agents are anticipated to play a
crucial role in the 6th Generation of wireless networks. Their seamless integration, cost …
crucial role in the 6th Generation of wireless networks. Their seamless integration, cost …
Feature-based Federated Transfer Learning: Communication Efficiency, Robustness and Privacy
In this paper, we propose feature-based federated transfer learning as a novel approach to
improve communication efficiency by reducing the uplink payload by multiple orders of …
improve communication efficiency by reducing the uplink payload by multiple orders of …
Communication-Efficient Personalized Federated Learning for Digital Twin in Heterogeneous Industrial IoT
Z Wang, X Ma, H Zhang, D Yuan - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
As an up-coming digitalization technology, the digital twin (DT) offers a viable
implementation for dynamic perception and intelligent decision-making in the industrial IoT …
implementation for dynamic perception and intelligent decision-making in the industrial IoT …
Optimized Lightweight Federated Learning for Botnet Detection in Smart Critical Infrastructure
S Popoola, R Ande, A Atayero, M Hammoudeh… - Authorea …, 2023 - techrxiv.org
In this paper, we propose an optimized lightweight Federated Deep Learning (FDL) method
for botnet attack detection in smart critical infrastructure. First, an optimization method is …
for botnet attack detection in smart critical infrastructure. First, an optimization method is …
Federated deep learning for botnet attack detection in IoT networks
SI Popoola - 2022 - e-space.mmu.ac.uk
The wide adoption of the Internet of Things (IoT) technology in various critical infrastructure
sectors has attracted the attention of cyber attackers. They exploit the vulnerabilities in IoT to …
sectors has attracted the attention of cyber attackers. They exploit the vulnerabilities in IoT to …
Federated Transfer Component Analysis Towards Effective VNF Profiling
The increasing concerns of knowledge transfer and data privacy challenge the traditional
gather-and-analyse paradigm in networks. Specifically, the intelligent orchestration of Virtual …
gather-and-analyse paradigm in networks. Specifically, the intelligent orchestration of Virtual …
A Comparative Analysis of Federated and Centralized Machine Learning for Intrusion Detection in IoT
The Internet of Things (IoT) plays a pivotal role in connecting diverse, resource-constrained,
and communication-capable smart devices across various domains, including smart cities, e …
and communication-capable smart devices across various domains, including smart cities, e …
梯度隐藏的安全聚类与隐私保护联邦学习.
李功丽， 马婧雯， 范云 - Application Research of Computers …, 2024 - search.ebscohost.com
Federatedlearningisakindofadvanceddistrib…, whichrealizesmulti party
cooperativetrainingwhileensuringtheuser'scontroloverthedata. However …
cooperativetrainingwhileensuringtheuser'scontroloverthedata. However …