Effect of the Sampling of a Dataset in the Hyperparameter Optimization Phase over the Efficiency of a Machine Learning Algorithm. - Noemí DeCastro-García; Ángel Luis Muñoz Castañeda; David Escudero García; Miguel V. Carriegos (Complex., 2019)

Optimal feature configuration for dynamic malware detection. - David Escudero García; Noemí DeCastro-García (Comput. Secur., 2021)

Application of Anomaly Detection Models to Malware Detection in the Presence of Concept Drift. - David Escudero García; Noemí DeCastro-García (HAIS, 2023)

Towards Supercomputing Categorizing the Maliciousness upon Cybersecurity Blacklists with Concept Drift. - Miguel V. Carriegos; Noemí DeCastro-García; David Escudero García (Comput. Math. Methods, 2023)

An effectiveness analysis of transfer learning for the concept drift problem in malware detection. - David Escudero García; Noemí DeCastro-García; Ángel Luis Muñoz Castañeda (Expert Syst. Appl., 2023)

Application of Transfer Learning to Online Models in Malware Detection. - David Escudero García; Noemí DeCastro-García (HAIS (1), 2024)

A mathematical analysis about the geo-temporal characterization of the multi-class maliciousness of an IP address. - Noemí DeCastro-García; David Escudero García; Miguel V. Carriegos (Wirel. Networks, 2024)

Transfer and online learning for IP maliciousness prediction in a concept drift scenario. - David Escudero García; Noemí DeCastro-García (Wirel. Networks, 2024)

Conformal prediction for labelling and updating online models in the presence of concept drift in cybersecurity. - David Escudero García; Noemí DeCastro-García (J. Inf. Secur. Appl., 2025)