Ángel Luis Perales Gómez

According to our database, Ángel Luis Perales Gómez authored at least 21 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Detection of Adversarial Attacks Using Deep Learning and Features Extracted From Interpretability Methods in Industrial Scenarios.

Ángel Luis Perales Gómez, Lorenzo Fernández Maimó, Alberto Huertas Celdrán, Félix J. García Clemente

IEEE Access, 2025

2024

Fedstellar: A Platform for Decentralized Federated Learning.

Enrique Tomás Martínez Beltrán, Ángel Luis Perales Gómez, Chao Feng, Pedro Miguel Sánchez Sánchez, Sergio López Bernal, Gérôme Bovet, Manuel Gil Pérez, Gregorio Martínez Pérez, Alberto Huertas Celdrán

Expert Syst. Appl., 2024

Corrigendum to "Fedstellar: A platform for decentralized federated learning" [Expert Syst. Appl. 242 (2024) 122861].

Enrique Tomás Martínez Beltrán, Ángel Luis Perales Gómez, Chao Feng, Pedro Miguel Sánchez Sánchez, Pedro Guijas Bravo, Sergio López Bernal, Gérôme Bovet, Manuel Gil Pérez, Gregorio Martínez Pérez, Alberto Huertas Celdrán

Expert Syst. Appl., 2024

A few-shot learning methodology for improving safety in industrial scenarios through universal self-supervised visual features and dense optical flow.

Juan Jesús Losada Del Olmo, Ángel Luis Perales Gómez, Pedro E. López-de-Teruel, Alberto Ruiz

Appl. Soft Comput., 2024

MeloDI: An Internet of Things Architecture to Evaluate Melon Quality by Means of Machine Learning Using Sensors Data and Drone Images.

Ángel Luis Perales Gómez, Juan Jesús Losada Del Olmo, Pedro E. López-de-Teruel, Alberto Ruiz, Félix J. García Clemente, Andrés Conesa Bueno

IEEE Access, 2024

Advancing Threat Detection in Fog Computing: A Comprehensive Approach to Real-Time Analysis and Model Generation.

Lucía Cuadrillero Paredes, Ángel Luis Perales Gómez, Óscar Cánovas, Lorenzo Fernández Maimó, Félix J. García Clemente

Proceedings of the 2024 9th International Conference on Fog and Mobile Edge Computing (FMEC), 2024

Enhacing Logistics with Computer Vision and Fog Computing-Driven Auto-ID Technologies.

Juan Jesús Losada Del Olmo, Ángel Luis Perales Gómez, Pedro E. López-de-Teruel Alcolea, Alberto Ruiz García, Félix J. García Clemente

Proceedings of the 2024 9th International Conference on Fog and Mobile Edge Computing (FMEC), 2024

2023

VAASI: Crafting valid and abnormal adversarial samples for anomaly detection systems in industrial scenarios.

Ángel Luis Perales Gómez, Lorenzo Fernández Maimó, Alberto Huertas Celdrán, Félix J. García Clemente

J. Inf. Secur. Appl., December, 2023

Behavioral fingerprinting to detect ransomware in resource-constrained devices.

Alberto Huertas Celdrán, Pedro Miguel Sánchez Sánchez, Jan von der Assen, Dennis Shushack, Ángel Luis Perales Gómez, Gérôme Bovet, Gregorio Martínez Pérez, Burkhard Stiller

Comput. Secur., December, 2023

An interpretable semi-supervised system for detecting cyberattacks using anomaly detection in industrial scenarios.

Ángel Luis Perales Gómez, Lorenzo Fernández Maimó, Alberto Huertas Celdrán, Félix J. García Clemente

IET Inf. Secur., July, 2023

SUSAN: A Deep Learning based anomaly detection framework for sustainable industry.

Ángel Luis Perales Gómez, Lorenzo Fernández Maimó, Alberto Huertas Celdrán, Félix J. García Clemente

Sustain. Comput. Informatics Syst., January, 2023

TemporalFED: Detecting Cyberattacks in Industrial Time-Series Data Using Decentralized Federated Learning.

Ángel Luis Perales Gómez, Enrique Tomás Martínez Beltrán, Pedro Miguel Sánchez Sánchez, Alberto Huertas Celdrán

CoRR, 2023

2022

FARMIT: continuous assessment of crop quality using machine learning and deep learning techniques for IoT-based smart farming.

Ángel Luis Perales Gómez, Pedro E. López-de-Teruel, Alberto Ruiz, Ginés García-Mateos, Gregorio Bernabé García, Félix J. García Clemente

Clust. Comput., 2022

A Methodology for Evaluating the Robustness of Anomaly Detectors to Adversarial Attacks in Industrial Scenarios.

Ángel Luis Perales Gómez, Lorenzo Fernández Maimó, Félix J. García Clemente, Javier Alejandro Maroto Morales, Alberto Huertas Celdrán, Gérôme Bovet

IEEE Access, 2022

2021

SafeMan: A unified framework to manage cybersecurity and safety in manufacturing industry.

Ángel Luis Perales Gómez, Lorenzo Fernández Maimó, Alberto Huertas Celdrán, Félix J. García Clemente, Manuel Gil Pérez, Gregorio Martínez Pérez

Softw. Pract. Exp., 2021

Crafting Adversarial Samples for Anomaly Detectors in Industrial Control Systems.

Ángel Luis Perales Gómez, Lorenzo Fernández Maimó, Alberto Huertas Celdrán, Félix J. García Clemente, Frances Cleary

Proceedings of the 12th International Conference on Ambient Systems, 2021

2020

BEHACOM.

Pedro Miguel Sánchez Sánchez, José María Jorquera Valero, Mattia Zago, Alberto Huertas Celdrán, Lorenzo Fernández Maimó, Eduardo López Bernal, Sergio López Bernal, Javier Martínez Valverde, Pantaleone Nespoli, Javier Pastor-Galindo, Ángel Luis Perales Gómez, Manuel Gil Pérez, Gregorio Martínez Pérez

Dataset, April, 2020

MADICS: A Methodology for Anomaly Detection in Industrial Control Systems.

Ángel Luis Perales Gómez, Lorenzo Fernández Maimó, Alberto Huertas Celdrán, Félix J. García Clemente

Symmetry, 2020

2019

Intelligent and Dynamic Ransomware Spread Detection and Mitigation in Integrated Clinical Environments.

Lorenzo Fernández Maimó, Alberto Huertas Celdrán, Ángel Luis Perales Gómez, Félix J. García Clemente, James Weimer, Insup Lee

Sensors, 2019

On the Generation of Anomaly Detection Datasets in Industrial Control Systems.

Ángel Luis Perales Gómez, Lorenzo Fernández Maimó, Alberto Huertas Celdrán, Félix J. García Clemente, Cristian Cadenas Sarmiento, Carlos Javier Del Canto Masa, Rubén Méndez Nistal

IEEE Access, 2019

2018

A Self-Adaptive Deep Learning-Based System for Anomaly Detection in 5G Networks.

Lorenzo Fernández Maimó, Ángel Luis Perales Gómez, Félix J. García Clemente, Manuel Gil Pérez, Gregorio Martínez Pérez

IEEE Access, 2018