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Ángel Luis Perales Gómez
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Year
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
2862018
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
1052019
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
832019
Madics: A methodology for anomaly detection in industrial control systems
ÁL Perales Gómez, L Fernández Maimó, A Huertas Celdrán, ...
Symmetry 12 (10), 1583, 2020
482020
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
252021
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
142022
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
132021
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
92024
LP, Clemente FJG, Pérez MG, Pérez GM
LF Maimó, Á Gómez
A self-adaptive deep learning-based system for anomaly detection in 5G …, 2018
72018
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
62023
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
52020
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
22023
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
22022
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
22022
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
22019
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
12023
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
Cyberattacks detection in industrial scenarios using Machine Learning and Deep Learning techniques
ÁL Perales Gómez
Proyecto de investigación:, 2021
2021
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Articles 1–20