Lorenzo
Fernandez Maimo
Profesores Titulares de Universidad
Angel Luis
Perales Gomez
Asociado a Tiempo Parcial
Publicaciones en las que colabora con Angel Luis Perales Gomez (18)
2024
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A Review of An Interpretable Semi-Supervised System for Detecting Cyberattacks Using Anomaly Detection in Industrial Scenarios
IX Jornadas Nacionales de Investigación En Ciberseguridad
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A Review of SUSAN: A Deep Learning based anomaly detection framework for sustainable industry
IX Jornadas Nacionales de Investigación En Ciberseguridad
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A Review of VAASI: Crafting Valid and Abnormal Adversarial Samples for Anomaly Detection Systems in Industrial Scenarios
IX Jornadas Nacionales de Investigación En Ciberseguridad
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Advancing Threat Detection in Fog Computing: A Comprehensive Approach to Real-Time Analysis and Model Generation
2024 9th International Conference on Fog and Mobile Edge Computing, FMEC 2024
2023
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An interpretable semi-supervised system for detecting cyberattacks using anomaly detection in industrial scenarios
IET Information Security, Vol. 17, Núm. 4, pp. 553-566
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SUSAN: A Deep Learning based anomaly detection framework for sustainable industry
Sustainable Computing: Informatics and Systems, Vol. 37
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VAASI: Crafting valid and abnormal adversarial samples for anomaly detection systems in industrial scenarios
Journal of Information Security and Applications, Vol. 79
2022
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A Methodology for Evaluating the Robustness of Anomaly Detectors to Adversarial Attacks in Industrial Scenarios
IEEE Access, Vol. 10, pp. 124582-124594
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Malware Detection in Industrial Scenarios Using Machine Learning and Deep Learning Techniques
Advances in Malware and Data-Driven Network Security, pp. 74-93
2021
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A Review of MADICS: A Methodology for Anomaly Detection in Industrial Control Systems
Investigación en Ciberseguridad
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Crafting adversarial samples for anomaly detectors in industrial control systems
Procedia Computer Science
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SafeMan: A unified framework to manage cybersecurity and safety in manufacturing industry
Software - Practice and Experience
2020
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BEHACOM - a dataset modelling users’ behaviour in computers
Data in Brief
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MADICS: A methodology for anomaly detection in industrial control systems
Symmetry, Vol. 12, Núm. 10
2019
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A Deep Learning-based System for Network Cyber Threat Detection
Machine Learning for Computer and Cyber Security, pp. 1-25
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Intelligent and Dynamic Ransomware Spread Detection and Mitigation in Integrated Clinical Environments
Sensors (Basel, Switzerland), Vol. 19, Núm. 5
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On the Generation of Anomaly Detection Datasets in Industrial Control Systems
IEEE Access, Vol. 7, pp. 177460-177473
2018
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A Self-Adaptive Deep Learning-Based System for Anomaly Detection in 5G Networks
IEEE Access, Vol. 6, pp. 7700-7712