Survey on federated learning threats: Concepts, taxonomy on attacks and defences, experimental study and challenges

N Rodríguez-Barroso, D Jiménez-López, MV Luzón… - Information …, 2023 - Elsevier
Federated learning is a machine learning paradigm that emerges as a solution to the privacy-
preservation demands in artificial intelligence. As machine learning, federated learning is …

Federated Learning for Urban Sensing Systems: A Comprehensive Survey on Attacks, Defences, Incentive Mechanisms, and Applications

A Kapoor, D Kumar - IEEE Communications Surveys & Tutorials, 2024 - ieeexplore.ieee.org
In recent years, advancements in Artificial Intelligence (AI), the Internet of Things (IoT) and
wireless technologies have propelled the evolution of smart cities. Urban sensing systems …

Securing the collective intelligence: a comprehensive review of federated learning security attacks and defensive strategies

V Kaushal, S Sharma - Knowledge and Information Systems, 2025 - Springer
Federated learning holds significant potential as a collaborative machine learning
technique, allowing multiple entities to work together on a collective model without the need …

Byzantine-robust variance-reduced federated learning over distributed non-iid data

J Peng, Z Wu, Q Ling, T Chen - Information Sciences, 2022 - Elsevier
We consider the federated learning problem where data on workers are not independent
and identically distributed (iid). During the learning process, an unknown number of …

DPFedBank: Crafting a Privacy-Preserving Federated Learning Framework for Financial Institutions with Policy Pillars

P He, C Lin, I Montoya - arxiv preprint arxiv:2410.13753, 2024 - arxiv.org
In recent years, the financial sector has faced growing pressure to adopt advanced machine
learning models to derive valuable insights while preserving data privacy. However, the …