Publications (14) Lorenzo Fernandez Maimo publications View referenced research data.

filter_list Artificial Intelligence

2025

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

    IEEE Access, Vol. 13, pp. 2705-2722

2023

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

    IET Information Security, Vol. 17, Núm. 4, pp. 553-566

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

    Sustainable Computing: Informatics and Systems, Vol. 37

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

    Journal of Information Security and Applications, Vol. 79

2022

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

    IEEE Access, Vol. 10, pp. 124582-124594

2021

  1. AuthCODE: A privacy-preserving and multi-device continuous authentication architecture based on machine and deep learning

    Computers and Security, Vol. 103

  2. Crafting adversarial samples for anomaly detectors in industrial control systems

    Procedia Computer Science

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

    Software - Practice and Experience

2020

  1. MADICS: A methodology for anomaly detection in industrial control systems

    Symmetry, Vol. 12, Núm. 10

2019

  1. Dynamic management of a deep learning-based anomaly detection system for 5G networks

    Journal of Ambient Intelligence and Humanized Computing, Vol. 10, Núm. 8, pp. 3083-3097

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

    Sensors (Basel, Switzerland), Vol. 19, Núm. 5

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

    IEEE Access, Vol. 7, pp. 177460-177473

2018

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

    IEEE Access, Vol. 6, pp. 7700-7712

2017

  1. On the performance of a deep learning-based anomaly detection system for 5G networks

    2017 IEEE SmartWorld Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation, SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017 - Conference Proceedings