Federated learning in edge computing: a systematic survey

HG Abreha, M Hayajneh, MA Serhani - Sensors, 2022‏ - mdpi.com
Edge Computing (EC) is a new architecture that extends Cloud Computing (CC) services
closer to data sources. EC combined with Deep Learning (DL) is a promising technology …

Federated learning for medical applications: A taxonomy, current trends, challenges, and future research directions

A Rauniyar, DH Hagos, D Jha… - IEEE Internet of …, 2023‏ - ieeexplore.ieee.org
With the advent of the Internet of Things (IoT), artificial intelligence (AI), machine learning
(ML), and deep learning (DL) algorithms, the landscape of data-driven medical applications …

Toward trustworthy ai: Blockchain-based architecture design for accountability and fairness of federated learning systems

SK Lo, Y Liu, Q Lu, C Wang, X Xu… - IEEE Internet of …, 2022‏ - ieeexplore.ieee.org
Federated learning is an emerging privacy-preserving AI technique where clients (ie,
organizations or devices) train models locally and formulate a global model based on the …

Responsible ai pattern catalogue: A collection of best practices for ai governance and engineering

Q Lu, L Zhu, X Xu, J Whittle, D Zowghi… - ACM Computing …, 2024‏ - dl.acm.org
Responsible Artificial Intelligence (RAI) is widely considered as one of the greatest scientific
challenges of our time and is key to increase the adoption of Artificial Intelligence (AI) …

[HTML][HTML] Lightweight federated learning for rice leaf disease classification using non independent and identically distributed images

M Aggarwal, V Khullar, N Goyal, A Alammari… - Sustainability, 2023‏ - mdpi.com
Rice (Oryza sativa L.) is a vital food source all over the world, contributing 15% of the protein
and 21% of the energy intake per person in Asia, where most rice is produced and …

A survey on heterogeneity taxonomy, security and privacy preservation in the integration of IoT, wireless sensor networks and federated learning

TM Mengistu, T Kim, JW Lin - Sensors, 2024‏ - mdpi.com
Federated learning (FL) is a machine learning (ML) technique that enables collaborative
model training without sharing raw data, making it ideal for Internet of Things (IoT) …

[HTML][HTML] Federatedtrust: A solution for trustworthy federated learning

PMS Sánchez, AH Celdrán, N **e, G Bovet… - Future Generation …, 2024‏ - Elsevier
The rapid expansion of the Internet of Things (IoT) and Edge Computing has presented
challenges for centralized Machine and Deep Learning (ML/DL) methods due to the …

[HTML][HTML] Comparative review of the intrusion detection systems based on federated learning: Advantages and open challenges

E Fedorchenko, E Novikova, A Shulepov - Algorithms, 2022‏ - mdpi.com
In order to provide an accurate and timely response to different types of the attacks, intrusion
and anomaly detection systems collect and analyze a lot of data that may include personal …