Publications
2019
Velasco-Mata, Javier; Fidalgo, Eduardo; González-Castro, Víctor; Alegre, Enrique; Blanco-Medina, Pablo
Botnet detection on TCP traffic using supervised machine learning Artículo de revista
En: Hybrid Artificial Intelligent Systems: 14th International Conference, HAIS 2019, León, Spain, September 4–6, 2019, Proceedings 14, pp. 444–455, 2019, (Publisher: Springer International Publishing).
Resumen | Enlaces | BibTeX | Etiquetas: Botnets, Classifiers, Cybersecurity, Datasets, machine learning
@article{velasco-mata_botnet_2019,
title = {Botnet detection on TCP traffic using supervised machine learning},
author = {Javier Velasco-Mata and Eduardo Fidalgo and Víctor González-Castro and Enrique Alegre and Pablo Blanco-Medina},
url = {https://link.springer.com/chapter/10.1007/978-3-030-29859-3_38},
year = {2019},
date = {2019-01-01},
journal = {Hybrid Artificial Intelligent Systems: 14th International Conference, HAIS 2019, León, Spain, September 4–6, 2019, Proceedings 14},
pages = {444–455},
abstract = {The rise of botnets on the Internet requires detecting their activity. Two datasets (TCP-Int and TCP-Sink) were created to evaluate traffic classifiers. Four Machine Learning models were tested, with Decision Tree achieving the best performance: 0.99 F1 score on TCP-Int and 0.99 AUC score on TCP-Sink.},
note = {Publisher: Springer International Publishing},
keywords = {Botnets, Classifiers, Cybersecurity, Datasets, machine learning},
pubstate = {published},
tppubtype = {article}
}
2018
Sánchez-González, Lidia; Fernández-Robles, Laura; Castejón-Limas, Manuel; Alfonso-Cendón, Javier; Pérez, Hilde; Quintián-Pardo, Hector; Corchado-Rodríguez, Emilio
Use of classifiers and recursive feature elimination to assess boar sperm viability Artículo de revista
En: Logic Journal of the IGPL, vol. 26, no 6, pp. 629–637, 2018, (Publisher: Oxford University Press).
Resumen | Enlaces | BibTeX | Etiquetas: Acrosome Reaction, Boar Sperm Cells, Classifiers, Dimension Reduction
@article{sanchez-gonzalez_use_2018,
title = {Use of classifiers and recursive feature elimination to assess boar sperm viability},
author = {Lidia Sánchez-González and Laura Fernández-Robles and Manuel Castejón-Limas and Javier Alfonso-Cendón and Hilde Pérez and Hector Quintián-Pardo and Emilio Corchado-Rodríguez},
url = {https://academic.oup.com/jigpal/article-abstract/26/6/629/5092723?login=true},
year = {2018},
date = {2018-01-01},
urldate = {2018-01-01},
journal = {Logic Journal of the IGPL},
volume = {26},
number = {6},
pages = {629–637},
abstract = {This paper evaluates the use of various classifiers to assess boar sperm cells and discriminate between intact or reacted acrosomes for fertility purposes. It also investigates the feasibility of applying dimension-reduction techniques to simplify the classification process. Four supervised classifiers were used: Extremely Randomized Trees, Random Forest, Support Vector Machines, and Gaussian Naive Bayes. The datasets contain features related to local gradients, gray levels, and standard deviations along sperm cell contours. The experiments showed that only 5 features out of 840 were needed for satisfactory results, as determined by veterinary experts.},
note = {Publisher: Oxford University Press},
keywords = {Acrosome Reaction, Boar Sperm Cells, Classifiers, Dimension Reduction},
pubstate = {published},
tppubtype = {article}
}