15 citations · 28 across the 7 of their papers we have counts for
7 papers
Latent Diffusion for Internet of Things Attack Data Generation in Intrusion Detection
Estela Sánchez-Carballo, Francisco M. Melgarejo-Meseguer, José Luis Rojo-Álvarez
Intrusion Detection Systems (IDSs) are a key component for protecting Internet of Things (IoT) environments. However, in Machine Learning-based (ML-based) IDSs, performance is ofte…
Explainable Autoencoder-Based Anomaly Detection in IEC 61850 GOOSE Networks
Dafne Lozano-Paredes, Luis Bote-Curiel, Juan Ramón Feijóo-Martínez +2
The IEC 61850 Generic Object-Oriented Substation Event (GOOSE) protocol plays a critical role in real-time protection and automation of digital substations, yet its lack of native…
Descriptor: Multi-Regional Cloud Honeypot Dataset (MURHCAD)
Enrique Feito-Casares, Ismael Gómez-Talal, José-Luis Rojo-Álvarez
This data article introduces a comprehensive, high-resolution honeynet dataset designed to support standalone analyses of global cyberattack behaviors. Collected over a continuous…
Learning Reconstructive Embeddings in Reproducing Kernel Hilbert Spaces via the Representer Theorem
Enrique Feito-Casares, Francisco M. Melgarejo-Meseguer, José-Luis Rojo-Álvarez
Motivated by the growing interest in representation learning approaches that uncover the latent structure of high-dimensional data, this work proposes new algorithms for reconstruc…
Understanding the Disparities in Mathematics Performance: An Interpretability-Based Examination
Ismael Gomez-Talal, Luis Bote-Curiel, Jose Luis Rojo-Alvarez
Problem. Educational disparities in Mathematics performance are a persistent challenge. This study aims to unravel the complex factors contributing to these disparities among stude…
Multivariate Feature Selection and Autoencoder Embeddings of Ovarian Cancer Clinical and Genetic Data
Luis Bote-Curiel, Sergio Ruiz-Llorente, Sergio Muñoz-Romero +4
This study explores a data-driven approach to discovering novel clinical and genetic markers in ovarian cancer (OC). Two main analyses were performed: (1) a nonlinear examination o…
A Unified SVM Framework for Signal Estimation
José Luis Rojo-Álvarez, Manel Martínez-Ramón, Jordi Muñoz-Marí +1
This paper presents a unified framework to tackle estimation problems in Digital Signal Processing (DSP) using Support Vector Machines (SVMs). The use of SVMs in estimation problem…