Listar GI-LIDIA - Artigos por autor "Fontenla-Romero, Óscar"

Mostrando ítems 1-7 de 7

    • A novel intelligent approach for man-in-the-middle attacks detection over internet of things environments based on message queuing telemetry transport 

      Michelena, Álvaro; Aveleira Mata, Jose Antonio; Jove, Esteban; Bayón Gutiérrez, Martín; Novais, Paulo; Fontenla-Romero, Óscar; Calvo-Rolle, José Luis; Alaiz Moretón, Héctor (Wiley, 2024)
      [Abstract]: One of the most common attacks is man-in-the-middle (MitM) which, due to its complex behaviour, is difficult to detect by traditional cyber-attack detection systems. MitM attacks on internet of things systems ...

    • A One-Class Classification method based on Expanded Non-Convex Hulls 

      Novoa-Paradela, David; Fontenla-Romero, Óscar; Guijarro-Berdiñas, Bertha (Elsevier, 2023)
      [Abstract]: This paper presents an intuitive, robust and efficient One-Class Classification algorithm. The method developed is called OCENCH (One-class Classification via Expanded Non-Convex Hulls) and bases its operation ...

    • Explained anomaly detection in text reviews: Can subjective scenarios be correctly evaluated? 

      Novoa-Paradela, David; Fontenla-Romero, Óscar; Guijarro-Berdiñas, Bertha (2024-07)
      In the current landscape, user opinions exert an unprecedented influence on the trajectory of companies. In the field of online review platforms, these opinions, transmitted through text reviews and numerical ratings, ...

    • Fast deep autoencoder for federated learning 

      Novoa-Paradela, David; Fontenla-Romero, Óscar; Guijarro-Berdiñas, Bertha (Elsevier Ltd, 2023-11)
      [Abstract]: This paper presents a novel, fast and privacy preserving implementation of deep autoencoders. DAEF (Deep AutoEncoder for Federated learning), unlike traditional neural networks, trains a deep autoencoder network ...

    • FedHEONN: Federated and homomorphically encrypted learning method for one-layer neural networks 

      Fontenla-Romero, Óscar; Guijarro-Berdiñas, Bertha; Hernández-Pereira, Elena; Pérez-Sánchez, Beatriz (Elsevier B.V., 2023)
      [Abstract]: Federated learning (FL) is a distributed approach to developing collaborative learning models from decentralized data. This is relevant to many real applications, such as in the field of the Internet of Things, ...

    • Machine Learning Techniques to Predict Different Levels of Hospital Care of CoVid-19 

      Hernández-Pereira, Elena; Fontenla-Romero, Óscar; Bolón-Canedo, Verónica; Cancela, Brais; Guijarro-Berdiñas, Bertha; Alonso-Betanzos, Amparo (Springer, 2022)
      [Abstract] In this study, we analyze the capability of several state of the art machine learning methods to predict whether patients diagnosed with CoVid-19 (CoronaVirus disease 2019) will need different levels of hospital ...

    • SOPRENE: Assessment of the Spanish Armada’s Predictive Maintenance Tool for Naval Assets 

      Fernández Barrero, David; Fontenla-Romero, Óscar; Lamas-López, Francisco; Novoa-Paradela, David; R-Moreno, María; Sanz, David (MDPI, 2021)
      [Abstract] Predictive maintenance has lately proved to be a useful tool for optimizing costs, performance and systems availability. Furthermore, the greater and more complex the system, the higher the benefit but also the ...