Distributed artificial intelligence empowered by end-edge-cloud computing: A survey

S Duan, D Wang, J Ren, F Lyu, Y Zhang… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
As the computing paradigm shifts from cloud computing to end-edge-cloud computing, it
also supports artificial intelligence evolving from a centralized manner to a distributed one …

Fl-defender: Combating targeted attacks in federated learning

NM Jebreel, J Domingo-Ferrer - Knowledge-Based Systems, 2023 - Elsevier
Federated learning (FL) enables learning a global machine learning model from data
distributed among a set of participating workers. This makes it possible (i) to train more …

[HTML][HTML] Security of federated learning with IoT systems: Issues, limitations, challenges, and solutions

JPA Yaacoub, HN Noura, O Salman - Internet of Things and Cyber-Physical …, 2023 - Elsevier
Abstract Federated Learning (FL, or Collaborative Learning (CL)) has surely gained a
reputation for not only building Machine Learning (ML) models that rely on distributed …

Flare: defending federated learning against model poisoning attacks via latent space representations

N Wang, Y **ao, Y Chen, Y Hu, W Lou… - … of the 2022 ACM on Asia …, 2022 - dl.acm.org
Federated learning (FL) has been shown vulnerable to a new class of adversarial attacks,
known as model poisoning attacks (MPA), where one or more malicious clients try to poison …

SafeFL: MPC-friendly framework for private and robust federated learning

T Gehlhar, F Marx, T Schneider… - 2023 IEEE Security …, 2023 - ieeexplore.ieee.org
Federated learning (FL) has gained widespread popularity in a variety of industries due to its
ability to locally train models on devices while preserving privacy. However, FL systems are …