Lorenzo
Fernandez Maimo
Profesores Titulares de Universidad
Publikationen, an denen er mitarbeitet Lorenzo Fernandez Maimo (39)
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
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Data fusion in neuromarketing: Multimodal analysis of biosignals, lifecycle stages, current advances, datasets, trends, and challenges
Information Fusion, Vol. 105
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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AuthCODE: A privacy-preserving and multi-device continuous authentication architecture based on machine and deep learning
Computers and Security, Vol. 103
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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