SCI2S at TASS 2018: Emotion Classification with Recurrent Neural Networks. - Nuria Rodríguez Barroso; Eugenio Martínez-Cámara; Francisco Herrera (TASS@SEPLN, 2018)

Deep Learning Hyper-parameter Tuning for Sentiment Analysis in Twitter based on Evolutionary Algorithms. - Eugenio Martínez Cámara; Nuria Rodríguez Barroso; Antonio R. Moya; José Alberto Fernández; Elena Romero; Francisco Herrera (FedCSIS, 2019)

Dynamic Federated Learning Model for Identifying Adversarial Clients. - Nuria Rodríguez Barroso; Eugenio Martínez-Cámara; María Victoria Luzón; Gerardo González-Seco; Miguel Ángel Veganzones; Francisco Herrera (CoRR, 2020)

Federated Learning and Differential Privacy: Software tools analysis, the Sherpa.ai FL framework and methodological guidelines for preserving data privacy. - Nuria Rodríguez Barroso; Goran Stipcich; Daniel Jiménez-López; José Antonio Ruiz-Millán; Eugenio Martínez-Cámara; Gerardo González-Seco; María Victoria Luzón; Miguel Angel Veganzones; Francisco Herrera (Inf. Fusion, 2020)

Dynamic defense against byzantine poisoning attacks in federated learning. - Nuria Rodríguez Barroso; Eugenio Martínez-Cámara; María Victoria Luzón; Francisco Herrera (Future Gener. Comput. Syst., 2022)

Backdoor attacks-resilient aggregation based on Robust Filtering of Outliers in federated learning for image classification. - Nuria Rodríguez Barroso; Eugenio Martínez-Cámara; María Victoria Luzón; Francisco Herrera (Knowl. Based Syst., 2022)

Can we infer the presence of Differential Privacy in Deep Learning models' weights? Towards more secure Deep Learning. - Daniel Jiménez-López; Nuria Rodríguez Barroso; María Victoria Luzón; Francisco Herrera (CoRR, 2023)

Survey on federated learning threats: Concepts, taxonomy on attacks and defences, experimental study and challenges. - Nuria Rodríguez Barroso; Daniel Jiménez-López; María Victoria Luzón; Francisco Herrera; Eugenio Martínez-Cámara (Inf. Fusion, 2023)

Defense Strategy against Byzantine Attacks in Federated Machine Learning: Developments towards Explainability. - Nuria Rodríguez Barroso; Javier Del Ser; María Victoria Luzón; Francisco Herrera (FUZZ, 2024)

RAB2-DEF: Dynamic and explainable defense against adversarial attacks in Federated Learning to fair poor clients. - Nuria Rodríguez Barroso; María Victoria Luzón; Francisco Herrera (CoRR, 2024)

Federated Learning for Exploiting Annotators' Disagreements in Natural Language Processing. - Nuria Rodríguez Barroso; Eugenio Martínez Cámara; José Camacho-Collados; María Victoria Luzón; Francisco Herrera (Trans. Assoc. Comput. Linguistics, 2024)

A Tutorial on Federated Learning from Theory to Practice: Foundations, Software Frameworks, Exemplary Use Cases, and Selected Trends. - María Victoria Luzón; Nuria Rodríguez Barroso; Alberto Argente-Garrido; Daniel Jiménez-López; Jose M. Moyano; Javier Del Ser; Weiping Ding 001; Francisco Herrera (IEEE CAA J. Autom. Sinica, 2024)

FLEX: Flexible Federated Learning Framework. - Francisco Herrera; Daniel Jiménez-López; Alberto Argente-Garrido; Nuria Rodríguez Barroso; Cristina Zuheros; Ignacio Aguilera-Martos; Beatriz Bello; Mario García-Márquez; María Victoria Luzón (Inf. Fusion, 2025)

Improving (α,f)-Byzantine resilience in federated learning via layerwise aggregation and cosine distance. - Mario García-Márquez; Nuria Rodríguez Barroso; María Victoria Luzón; Francisco Herrera (Knowl. Based Syst., 2025)

Krum Federated Chain (KFC): Using blockchain to defend against adversarial attacks in Federated Learning. - Mario García-Márquez; Nuria Rodríguez Barroso; María Victoria Luzón; Francisco Herrera (CoRR, 2025)

Membership Inference Attacks fueled by Few-Short Learning to detect privacy leakage tackling data integrity. - Daniel Jiménez-López; Nuria Rodríguez Barroso; María Victoria Luzón; Francisco Herrera (CoRR, 2025)

Addressing Data Quality Decompensation in Federated Learning via Dynamic Client Selection. - Qinjun Fei; Nuria Rodríguez Barroso; María Victoria Luzón; Zhongliang Zhang; Francisco Herrera (CoRR, 2025)

Challenges of Trustworthy Federated Learning: What's Done, Current Trends and Remaining Work. - Nuria Rodríguez Barroso; Mario García-Márquez; María Victoria Luzón; Francisco Herrera (CoRR, 2025)