1. Digitum: Repositorio Institucional de la Universidad de Murcia

Buscar por Autor García Clemente, Félix J.

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A_Self-Adaptive_Deep_Learning-Based_System_for_Anomaly_Detection_in_5G_Networks.pdf.jpg7-feb-2018-A self-adaptive deep learning-based system for anomaly detection in 5G networks
sensors-19-01114-1.pdf.jpg5-mar-2019-Intelligent and dynamic ransomware spread detection and mitigation in integrated clinical environments
On_the_Generation_of_Anomaly_Detection_Datasets_in_Industrial_Control_Systems.pdf.jpg6-dic-2019-On the generation of anomaly detection datasets in industrial control systems
_Preprint__SafeMan__A_Unified_Framework_to_Manage_Cybersecurity_and_Safety_in_Manufacturing_Industry.pdf.jpg6-ago-2020-SafeMan: a unified framework to manage cybersecurity and safety in manufacturing industry
symmetry-12-01583-5.pdf.jpg23-sep-2020-Madics: A methodology for anomaly detection in industrial control systems
A_Methodology_for_Evaluating_the_Robustness_of_Anomaly_Detectors_to_Adversarial_Attacks_in_Industrial_Scenarios.pdf.jpg28-nov-2022-A methodology for evaluating the robustness of anomaly detectors to adversarial attacks in industrial scenarios
1-s2.0-S2210537922001731-main.pdf.jpg5-ene-2023-SUSAN: a deep learning based anomaly detection framework for sustainable industry
1-s2.0-S2214212623002314-main.pdf.jpgdic-2023-VAASI: Crafting valid and abnormal adversarial samples for anomaly detection systems in industrial scenarios
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