Federated Learning and Differential Privacy: Software tools analysis, the Sherpa. ai FL framework and methodological guidelines for preserving data privacy N Rodríguez-Barroso, G Stipcich, D Jiménez-López, JA Ruiz-Millán, ... Information Fusion 64, 270-292, 2020 | 113 | 2020 |
Survey on federated learning threats: Concepts, taxonomy on attacks and defences, experimental study and challenges N Rodríguez-Barroso, D Jiménez-López, MV Luzón, F Herrera, ... Information Fusion 90, 148-173, 2023 | 110 | 2023 |
A tutorial on federated learning from theory to practice: Foundations, software frameworks, exemplary use cases, and selected trends MV Luzón, N Rodríguez-Barroso, A Argente-Garrido, D Jiménez-López, ... IEEE/CAA Journal of Automatica Sinica 11 (4), 824-850, 2024 | 2 | 2024 |
FLEX: FLEXible Federated Learning Framework F Herrera, D Jiménez-López, A Argente-Garrido, N Rodríguez-Barroso, ... arXiv preprint arXiv:2404.06127, 2024 | | 2024 |
Can we infer the presence of Differential Privacy in Deep Learning models' weights? Towards more secure Deep Learning M Victoria arXiv preprint arXiv:2311.11717, 2023 | | 2023 |