Decentralized federated learning: Fundamentals, state of the art, frameworks, trends, and challenges

ETM Beltrán, MQ Pérez, PMS Sánchez… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
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 …

A survey on trustworthy edge intelligence: From security and reliability to transparency and sustainability

X Wang, B Wang, Y Wu, Z Ning… - … Surveys & Tutorials, 2024 - ieeexplore.ieee.org
Edge Intelligence (EI) integrates Edge Computing (EC) and Artificial Intelligence (AI) to push
the capabilities of AI to the network edge for real-time, efficient and secure intelligent …

Trust in edge-based internet of things architectures: state of the art and research challenges

L Fotia, F Delicato, G Fortino - ACM Computing Surveys, 2023 - dl.acm.org
The Internet of Things (IoT) aims to enable a scenario where smart objects, inserted into
information networks, supply smart services for human beings. The introduction of edge …

Trustworthy federated learning via blockchain

Z Yang, Y Shi, Y Zhou, Z Wang… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
The safety-critical scenarios of artificial intelligence (AI), such as autonomous driving,
Internet of Things, smart healthcare, etc., have raised critical requirements of trustworthy AI …

Advanced deep learning models for 6G: overview, opportunities and challenges

L Jiao, Y Shao, L Sun, F Liu, S Yang, W Ma, L Li… - IEEE …, 2024 - ieeexplore.ieee.org
The advent of the sixth generation of mobile communications (6G) ushers in an era of
heightened demand for advanced network intelligence to tackle the challenges of an …

Anti-Counterfeiting and Traceability Consensus Algorithm Based on Weightage to Contributors in a Food Supply Chain of Industry 4.0

J Tan, SB Goyal, A Singh Rajawat, T Jan, N Azizi… - Sustainability, 2023 - mdpi.com
Supply chain management can significantly benefit from contemporary technologies. Among
these technologies, blockchain is considered suitable for anti-counterfeiting and traceability …

Trusted AI in multiagent systems: An overview of privacy and security for distributed learning

C Ma, J Li, K Wei, B Liu, M Ding, L Yuan… - Proceedings of the …, 2023 - ieeexplore.ieee.org
Motivated by the advancing computational capacity of distributed end-user equipment (UE),
as well as the increasing concerns about sharing private data, there has been considerable …

Improved modulation recognition using personalized federated learning

R Rahman, DC Nguyen - IEEE Transactions on Vehicular …, 2024 - ieeexplore.ieee.org
There are various types of signals around us and recognizing the signals allows a network
system to effectively and efficiently transmit from the sender to the receiver. Signals can be …

Secure and scalable blockchain-based federated learning for cryptocurrency fraud detection: A systematic review

AA Ahmed, O Alabi - IEEE Access, 2024 - ieeexplore.ieee.org
With the wide adoption of cryptocurrency, blockchain technologies have become the
foundation of such digital currencies. However, this adoption has been accompanied by a …

A survey of state-of-the-art on edge computing: Theoretical models, technologies, directions, and development paths

B Liu, Z Luo, H Chen, C Li - IEEE Access, 2022 - ieeexplore.ieee.org
In order to describe the roadmap of current edge computing research activities, we first
address a brief overview of the most advanced edge computing surveys published in the last …