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 …

Federated machine learning: Survey, multi-level classification, desirable criteria and future directions in communication and networking systems

OA Wahab, A Mourad, H Otrok… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
The communication and networking field is hungry for machine learning decision-making
solutions to replace the traditional model-driven approaches that proved to be not rich …

A survey on security and privacy of federated learning

V Mothukuri, RM Parizi, S Pouriyeh, Y Huang… - Future Generation …, 2021 - Elsevier
Federated learning (FL) is a new breed of Artificial Intelligence (AI) that builds upon
decentralized data and training that brings learning to the edge or directly on-device. FL is a …

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: A survey on enabling technologies, protocols, and applications

M Aledhari, R Razzak, RM Parizi, F Saeed - IEEE Access, 2020 - ieeexplore.ieee.org
This paper provides a comprehensive study of Federated Learning (FL) with an emphasis
on enabling software and hardware platforms, protocols, real-life applications and use …

Federated learning meets blockchain in edge computing: Opportunities and challenges

DC Nguyen, M Ding, QV Pham… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
Mobile-edge computing (MEC) has been envisioned as a promising paradigm to handle the
massive volume of data generated from ubiquitous mobile devices for enabling intelligent …

Blockchain-federated-learning and deep learning models for covid-19 detection using ct imaging

R Kumar, AA Khan, J Kumar, NA Golilarz… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
With the increase of COVID-19 cases worldwide, an effective way is required to diagnose
COVID-19 patients. The primary problem in diagnosing COVID-19 patients is the shortage …

Low-latency federated learning and blockchain for edge association in digital twin empowered 6G networks

Y Lu, X Huang, K Zhang, S Maharjan… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Emerging technologies, such as digital twins and 6th generation (6G) mobile networks, have
accelerated the realization of edge intelligence in industrial Internet of Things (IIoT). The …

Blockchain-enabled secure data sharing scheme in mobile-edge computing: An asynchronous advantage actor–critic learning approach

L Liu, J Feng, Q Pei, C Chen, Y Ming… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Mobile-edge computing (MEC) plays a significant role in enabling diverse service
applications by implementing efficient data sharing. However, the unique characteristics of …

Federated learning for vehicular internet of things: Recent advances and open issues

Z Du, C Wu, T Yoshinaga, KLA Yau… - IEEE Open Journal of …, 2020 - ieeexplore.ieee.org
Federated learning (FL) is a distributed machine learning approach that can achieve the
purpose of collaborative learning from a large amount of data that belong to different parties …