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FL-Incentivizer: FL-NFT and FL-Tokens for Federated Learning Model Trading and Training

IEEE Access, 2023
Federated learning (FL) is an on-device distributed learning scheme that does not require training devices to transfer their data to a centralized facility. The goal of federated learning is to learn a global model over several iterations.
Umer Majeed, Latif U. Khan, Sheikh Salman Hassan, Zhu Han, Choong Seon Hong   +4 more
doaj   +2 more sources

Blockchain-Based Decentralized Federated Learning Method in Edge Computing Environment

Applied Sciences, 2023
In recent years, federated learning has been able to provide an effective solution for data privacy protection, so it has been widely used in financial, medical, and other fields.
Song Liu, Xiong Wang, Longshuo Hui, Weiguo Wu   +3 more
doaj   +1 more source

Decentralised Federated Learning for Hospital Networks With Application to COVID-19 Detection

IEEE Access, 2022
Federated Learning (FL) is a distributed machine learning technique which enables local learning of global machine learning models without the need of exchanging data.
Alessandro Giuseppi, Sabato Manfredi, Danilo Menegatti, Cecilia Poli, Antonio Pietrabissa   +4 more
doaj   +1 more source

Federated Learning: A Distributed Shared Machine Learning Method

Complexity, 2021
Federated learning (FL) is a distributed machine learning (ML) framework. In FL, multiple clients collaborate to solve traditional distributed ML problems under the coordination of the central server without sharing their local private data with others ...
Kai Hu, Yaogen Li, Min Xia, Jiasheng Wu, Meixia Lu, Shuai Zhang, Liguo Weng   +6 more
doaj   +1 more source

Metaheuristics Algorithm-Based Minimization of Communication Costs in Federated Learning

IEEE Access, 2023
The Federated learning (FL) technique resolves the issue of training machine learning (ML) techniques on distributed networks, including the huge volume of modern smart devices.
Mohamed Ahmed Elfaki, Haya Mesfer Alshahrani, Khalid Mahmood, Rana Alabdan, Mofadal Alymani, Hussain Alshahrani, Abdelwahed Motwakel, Amani A. Alneil   +7 more
doaj   +1 more source

Federated Learning via Augmented Knowledge Distillation for Heterogenous Deep Human Activity Recognition Systems

Sensors, 2022
Deep learning-based Human Activity Recognition (HAR) systems received a lot of interest for health monitoring and activity tracking on wearable devices.
Gad Gad, Zubair Fadlullah
doaj   +1 more source

New Generation Federated Learning

Sensors, 2022
With the development of the Internet of things (IoT), federated learning (FL) has received increasing attention as a distributed machine learning (ML) framework that does not require data exchange. However, current FL frameworks follow an idealized setup
Boyuan Li, Shengbo Chen, Zihao Peng
doaj   +1 more source

Research on federated learning approach based on local differential privacy

Tongxin xuebao, 2022
As a type of collaborative machine learning framework, federated learning is capable of preserving private data from participants while training the data into useful models.Nevertheless, from a viewpoint of information theory, it is still vulnerable for ...
Haiyan KANG, Yuanrui JI
doaj   +2 more sources

Secure Smart Communication Efficiency in Federated Learning: Achievements and Challenges

Applied Sciences, 2022
Federated learning (FL) is known to perform machine learning tasks in a distributed manner. Over the years, this has become an emerging technology, especially with various data protection and privacy policies being imposed.
Seyedamin Pouriyeh, Osama Shahid, Reza M. Parizi, Quan Z. Sheng, Gautam Srivastava, Liang Zhao, Mohammad Nasajpour   +6 more
doaj   +1 more source

Privacy-Preserving Detection of Tampered Radio-Frequency Transmissions Utilizing Federated Learning in LoRa Networks

Sensors
LoRa networks, widely adopted for low-power, long-range communication in IoT applications, face critical security concerns as radio-frequency transmissions are increasingly vulnerable to tampering.
Nurettin Selcuk Senol, Mohamed Baza, Amar Rasheed, Maazen Alsabaan   +3 more
doaj   +1 more source