Now showing items 1-4 of 4

    • A survey of deep learning techniques for cybersecurity in mobile networks 

      Rodríguez Luna, Eva; Otero Calviño, Beatriz; Gutiérrez Escobar, Norma; Canal Corretger, Ramon (2021-06-07)
      Open Access
      The widespread use of mobile devices, as well as the increasing popularity of mobile services has raised serious cybersecurity challenges. In the last years, the number of cyberattacks has grown dramatically, as well as ...
    • Long short-term memory networks for earthquake detection in Venezuelan regions 

      Mus León, Sergi; Gutiérrez Escobar, Norma; Tous Liesa, Rubén; Otero Calviño, Beatriz; Cruz de la Cruz, Stalin Leonel; Llácer Giner, David; Alvarado Bermúdez, Leonardo; Rojas, Otilio (Springer, 2019)
      Conference lecture
      Open Access
      Reliable earthquake detection and location algorithms are necessary to properly catalog and analyze the continuously growing seismic records. This paper reports the results of applying Long Short-Term Memory (LSTM) networks ...
    • Malicious website detection through deep learning algorithms 

      Gutiérrez Escobar, Norma; Otero Calviño, Beatriz; Rodríguez Luna, Eva; Canal Corretger, Ramon (Springer Nature, 2022)
      Conference report
      Restricted access - publisher's policy
      Traditional methods that detect malicious websites, such as blacklists, do not update frequently, and they cannot detect new attackers. A system capable of detecting malicious activity using Deep Learning (DL) has been ...
    • Privacy preserving deep learning framework in fog computing 

      Gutiérrez Escobar, Norma; Rodríguez Luna, Eva; Mus León, Sergi; Otero Calviño, Beatriz; Canal Corretger, Ramon (Springer, 2020)
      Conference report
      Open Access
      Nowadays, the widespread use of mobile devices has raised serious cybersecurity challenges. Mobile services and applications use deep learning (DL) models for the modelling, classification and recognition of complex data, ...