| A self-adaptive deep learning-based system for anomaly detection in 5G networks LF Maimó, ÁLP Gómez, FJG Clemente, MG Pérez, GM Pérez Ieee Access 6, 7700-7712, 2018 | 301 | 2018 |
| Intelligent and dynamic ransomware spread detection and mitigation in integrated clinical environments L Fernandez Maimo, A Huertas Celdran, AL Perales Gomez, ... Sensors 19 (5), 1114, 2019 | 117 | 2019 |
| On the generation of anomaly detection datasets in industrial control systems ÁLP Gómez, LF Maimó, AH Celdrán, FJG Clemente, CC Sarmiento, ... IEEE Access 7, 177460-177473, 2019 | 89 | 2019 |
| Madics: A methodology for anomaly detection in industrial control systems ÁL Perales Gómez, L Fernández Maimó, A Huertas Celdrán, ... Symmetry 12 (10), 1583, 2020 | 52 | 2020 |
| SafeMan: A unified framework to manage cybersecurity and safety in manufacturing industry ÁL Perales Gómez, L Fernández Maimó, A Huertas Celdrán, ... Software: Practice and Experience 51 (3), 607-627, 2021 | 26 | 2021 |
| FARMIT: continuous assessment of crop quality using machine learning and deep learning techniques for IoT-based smart farming ÁL Perales Gómez, PE López-de-Teruel, A Ruiz, G García-Mateos, ... Cluster Computing 25 (3), 2163-2178, 2022 | 19 | 2022 |
| Crafting adversarial samples for anomaly detectors in industrial control systems ÁLP Gómez, LF Maimó, AH Celdrán, FJG Clemente, F Cleary Procedia Computer Science 184, 573-580, 2021 | 16 | 2021 |
| Fedstellar: A platform for decentralized federated learning ETM Beltrán, ÁLP Gómez, C Feng, PMS Sánchez, SL Bernal, G Bovet, ... Expert Systems with Applications 242, 122861, 2024 | 15 | 2024 |
| SUSAN: A Deep Learning based anomaly detection framework for sustainable industry ÁLP Gómez, LF Maimó, AH Celdrán, FJG Clemente Sustainable Computing: Informatics and Systems 37, 100842, 2023 | 12 | 2023 |
| LP, Clemente FJG, Pérez MG, Pérez GM LF Maimó, Á Gómez A self-adaptive deep learning-based system for anomaly detection in 5G …, 2018 | 7 | 2018 |
| BEHACOM-a dataset modelling users’ behaviour in computers PMS Sánchez, JMJ Valero, M Zago, AH Celdrán, LF Maimó, EL Bernal, ... Data in Brief 31, 105767, 2020 | 6 | 2020 |
| Behavioral fingerprinting to detect ransomware in resource-constrained devices AH Celdrán, PMS Sánchez, J von der Assen, D Shushack, ÁLP Gómez, ... Computers & Security 135, 103510, 2023 | 5 | 2023 |
| A methodology for evaluating the robustness of anomaly detectors to adversarial attacks in industrial scenarios ÁLP Gómez, LF Maimó, FJG Clemente, JAM Morales, AH Celdrán, ... Ieee Access 10, 124582-124594, 2022 | 3 | 2022 |
| TemporalFED: Detecting cyberattacks in industrial time-series data using decentralized federated learning ÁLP Gómez, ETM Beltrán, PMS Sánchez, AH Celdrán arXiv preprint arXiv:2308.03554, 2023 | 2 | 2023 |
| Malware Detection in Industrial Scenarios Using Machine Learning and Deep Learning Techniques ÁLP Gómez, LF Maimó, AH Celdrán, FJG Clemente Advances in Malware and Data-Driven Network Security, 74-93, 2022 | 2 | 2022 |
| A deep learning-based system for network cyber threat detection ALP Gomez, LF Maimó, FJG Clemente Machine Learning for Computer and Cyber Security, 1-25, 2019 | 2 | 2019 |
| Corrigendum to “Fedstellar: A platform for decentralized federated learning”[Expert Syst. Appl. 242 (2024) 122861] ETM Beltrán, ÁLP Gómez, C Feng, PMS Sánchez, PG Bravo, SL Bernal, ... Expert Systems with Applications 251, 124165, 2024 | | 2024 |
| Behavioral fingerprinting to detect ransomware in resource-constrained devices A Huertas Celdrán, PM Sánchez Sánchez, J von der Assen, D Shushack, ... | | 2023 |
| VAASI: Crafting valid and abnormal adversarial samples for anomaly detection systems in industrial scenarios ALP Gómez, LF Maimó, AH Celdrán, FJG Clemente Journal of Information Security and Applications 79, 103647, 2023 | | 2023 |
| An interpretable semi‐supervised system for detecting cyberattacks using anomaly detection in industrial scenarios ÁL Perales Gómez, L Fernández Maimó, A Huertas Celdrán, ... IET Information Security 17 (4), 553-566, 2023 | | 2023 |
