Federated Learning Ensemble Voting-Based Methods to Deal with Non-IID and Imbalanced Data in Cybersecurity

Bruno H. Meyer; Michele Nogueira; Wagner M. Nunan Zola; Aurora Pozo

doi:10.14201/adcaij.32905

Federated Learning Ensemble Voting-Based Methods to Deal with Non-IID and Imbalanced Data in Cybersecurity

Bruno H. Meyer

Department of Informatics (UFPR), Curitiba, Brazil bruno.meyer[at]ufpr.br
Michele Nogueira

Department of Computer Science (UFMG)
Wagner M. Nunan Zola

Department of Informatics (UFPR), Curitiba, Brazil
Aurora Pozo

Department of Informatics (UFPR), Curitiba, Brazil

https://doi.org/10.14201/adcaij.32905

Metrics

246 Views

445 Downloads

691 Total

How to Cite

Meyer, B. H., Nogueira, M., Nunan Zola, W. M., & Pozo, A. (2026). Federated Learning Ensemble Voting-Based Methods to Deal with Non-IID and Imbalanced Data in Cybersecurity. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 14, e32905. https://doi.org/10.14201/adcaij.32905

Download Citation

Editorial dates

Submitted:

19-02-2025

Acceptance:

08-02-2026

Published:

24-03-2026

Issue

Vol. 14 (2025)

Section

Articles

Keywords

Federated Learning
ensemble models
cybersecurity

Supporting agencies

This research didn't have any funding

License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

You are free to:

Share — copy and redistribute the material in any medium or format
Adapt — remix, transform, and build upon the material
The licensor cannot revoke these freedoms as long as you follow the license terms.

Under the following terms:

Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
NonCommercial — You may not use the material for commercial purposes.
ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Notices:

You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation.

No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.