Pedro Miguel Sanchez Sanchez-rekin lankidetzan egindako argitalpenak (63)

2024

  1. A Summary of Adversarial Attacks and Defenses on ML- and Hardware-based IoT Device Fingerprinting and Identification

    IX Jornadas Nacionales de Investigación En Ciberseguridad

  2. A Summary of RansomAI: AI-powered Ransomware for Stealthy Encryption

    IX Jornadas Nacionales de Investigación En Ciberseguridad

  3. Adversarial attacks and defenses on ML- and hardware-based IoT device fingerprinting and identification

    Future Generation Computer Systems, Vol. 152, pp. 30-42

  4. Analyzing the robustness of decentralized horizontal and vertical federated learning architectures in a non-IID scenario

    Applied Intelligence, Vol. 54, Núm. 8, pp. 6637-6653

  5. Corrigendum to “Fedstellar: A platform for decentralized federated learning” [Expert Syst. Appl. 242 (2024) 122861] (S0957417423033638), (10.1016/j.eswa.2023.122861)

    Expert Systems with Applications

  6. CyberSpec: Behavioral Fingerprinting for Intelligent Attacks Detection on Crowdsensing Spectrum Sensors

    IEEE Transactions on Dependable and Secure Computing, Vol. 21, Núm. 1, pp. 284-297

  7. Evaluating the impact of contextual information on the performance of intelligent continuous authentication systems

    ACM International Conference Proceeding Series

  8. FederatedTrust: A solution for trustworthy federated learning

    Future Generation Computer Systems, Vol. 152, pp. 83-98

  9. Fedstellar: A Platform for Decentralized Federated Learning

    Expert Systems with Applications, Vol. 242

  10. Mitigación de Ataques Bizantinos usando Modelos Históricos en Aprendizaje Federado Descentralizado

    IX Jornadas Nacionales de Investigación En Ciberseguridad

  11. Mitigating communications threats in decentralized federated learning through moving target defense

    Wireless Networks

  12. RL and Fingerprinting to Select Moving Target Defense Mechanisms for Zero-Day Attacks in IoT

    IEEE Transactions on Information Forensics and Security, Vol. 19, pp. 5520-5529

  13. Robust Federated Learning for execution time-based device model identification under label-flipping attack

    Cluster Computing, Vol. 27, Núm. 1, pp. 313-324

  14. Single-board device individual authentication based on hardware performance and autoencoder transformer models

    Computers and Security, Vol. 137

  15. Studying the Robustness of Anti-Adversarial Federated Learning Models Detecting Cyberattacks in IoT Spectrum Sensors

    IEEE Transactions on Dependable and Secure Computing, Vol. 21, Núm. 2, pp. 573-584

  16. Unlocking the Potential of Knowledge Graphs: A Cyber Defense Ontology for a Knowledge Representation and Reasoning System

    ACM International Conference Proceeding Series

2023

  1. A Framework Quantifying Trustworthiness of Supervised Machine and Deep Learning Models

    CEUR Workshop Proceedings

  2. A Lightweight Moving Target Defense Framework for Multi-purpose Malware Affecting IoT Devices

    IEEE International Conference on Communications

  3. A Review of "Toward Pre-standardization of Reputation-based Trust Models Beyond 5G"

    Actas de las VIII Jornadas Nacionales de Investigación en Ciberseguridad: Vigo, 21 a 23 de junio de 2023

  4. A Summary of Privacy-preserving and Syscall-based Intrusion Detection System for IoT Sensors Affected by Data Falsification Attacks

    Actas de las VIII Jornadas Nacionales de Investigación en Ciberseguridad: Vigo, 21 a 23 de junio de 2023