Decentralized federated learning: Fundamentals, state of the art, frameworks, trends, and challenges
In recent years, Federated Learning (FL) has gained relevance in training collaborative
models without sharing sensitive data. Since its birth, Centralized FL (CFL) has been the …
models without sharing sensitive data. Since its birth, Centralized FL (CFL) has been the …
[HTML][HTML] Blockchain integration in the era of industrial metaverse
Blockchain can be realized as a distributed and decentralized database, also known as a
“distributed ledger,” that is shared among the nodes of a computer network. Blockchain is a …
“distributed ledger,” that is shared among the nodes of a computer network. Blockchain is a …
Lightweight privacy and security computing for blockchained federated learning in iot
M Fan, K Ji, Z Zhang, H Yu… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
The development of Internet of Things (IoT) makes human life more intelligent, and the
interconnection of all things has become a reality. However, the surge in the number of …
interconnection of all things has become a reality. However, the surge in the number of …
Predicting the core determinants of cloud-edge computing adoption (CECA) for sustainable development in the higher education institutions of Africa: A high order …
Aims In the recent past, many studies have been conducted to elucidate the determinants
affecting cloud computing adoption at different institutional levels. The study aims to identify …
affecting cloud computing adoption at different institutional levels. The study aims to identify …
Evaluating the interrelationships of industrial 5.0 development factors using an integration approach of Fermatean Fuzzy Logic
The maturation of the Industry 4.0 concept has brought numerous benefits to human society.
However, it is not without its challenges, including neglect of worker welfare, vulnerability of …
However, it is not without its challenges, including neglect of worker welfare, vulnerability of …
[HTML][HTML] Anonymous federated learning via named-data networking
Federated Learning (FL) represents the de facto approach for distributed training of machine
learning models. Nevertheless, researchers have identified several security and privacy FL …
learning models. Nevertheless, researchers have identified several security and privacy FL …
[HTML][HTML] Mitigating communications threats in decentralized federated learning through moving target defense
ET Martínez Beltrán, PM Sánchez Sánchez… - Wireless …, 2024 - Springer
Abstract The rise of Decentralized Federated Learning (DFL) has enabled the training of
machine learning models across federated participants, fostering decentralized model …
machine learning models across federated participants, fostering decentralized model …
A novel federated multi-view clustering method for unaligned and incomplete data fusion
Recently, federated multi-view clustering (FedMVC) has emerged as a powerful tool to
uncover complementary cluster structures across distributed clients, gaining significant …
uncover complementary cluster structures across distributed clients, gaining significant …
GRU-based digital twin framework for data allocation and storage in IoT-enabled smart home networks
In recent years, the Internet of Things (IoT) devices utilization with Information
Communication Technology (ICT) has grown exponentially in various Smart City …
Communication Technology (ICT) has grown exponentially in various Smart City …
Ransomware-based cyber attacks: A comprehensive survey
Abstract Internet of Things (IoT) and sensor devices have been connected due to the
development of the IoT and Information Communication Technology (ICT). It offers automatic …
development of the IoT and Information Communication Technology (ICT). It offers automatic …