Evaluating Federated Learning for intrusion detection in Internet of Things: Review and challenges. - Enrique Mármol Campos; Pablo Fernández Saura; Aurora González-Vidal; José Luis Hernández-Ramos; Jorge Bernal Bernabé; Gianmarco Baldini; Antonio F. Skarmeta (Comput. Networks, 2022)

Federated Cyberattack Detection for Internet of Things-Enabled Smart Cities. - Sara Nieves Matheu; Enrique Mármol Campos; José Luis Hernández-Ramos; Antonio F. Skarmeta; Gianmarco Baldini (Computer, 2022)

Federated Transfer Learning for Energy Efficiency in Smart Buildings. - Enrique Mármol Campos; Aurora González-Vidal; José Luis Hernández-Ramos; Antonio F. Skarmeta (INFOCOM Workshops, 2023)

Intrusion Detection Based on Privacy-Preserving Federated Learning for the Industrial IoT. - Pedro Ruzafa Alcazar; Pablo Fernández Saura; Enrique Mármol Campos; Aurora González-Vidal; José Luis Hernández-Ramos; Jorge Bernal Bernabé; Antonio F. Skarmeta (IEEE Trans. Ind. Informatics, 2023)

Misbehavior detection in intelligent transportation systems based on federated learning. - Enrique Mármol Campos; José Luis Hernández-Ramos; Aurora González-Vidal; Gianmarco Baldini; Antonio F. Skarmeta (Internet Things, 2024)

FedRDF: A Robust and Dynamic Aggregation Function Against Poisoning Attacks in Federated Learning. - Enrique Mármol Campos; Aurora González-Vidal; José Luis Hernández-Ramos; Antonio F. Skarmeta (IEEE Trans. Emerg. Top. Comput., 2025)

Federated learning for misbehaviour detection with variational autoencoders and Gaussian mixture models. - Enrique Mármol Campos; Aurora González-Vidal; José Luis Hernández-Ramos; Antonio F. Skarmeta (Int. J. Inf. Sec., 2025)

Intrusion Detection Based on Federated Learning: A Systematic Review. - José Luis Hernández-Ramos; Georgios Karopoulos; Efstratios Chatzoglou; Vasileios Kouliaridis; Enrique Mármol Campos; Aurora González-Vidal; Georgios Kambourakis (ACM Comput. Surv., 2025)