Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Velasco Mata, Javier"'
Botnets are one of the online threats with the biggest presence, causing billionaire losses to global economies. Nowadays, the increasing number of devices connected to the Internet makes it necessary to analyze large amounts of network traffic data.
Externí odkaz:
http://arxiv.org/abs/2107.02896
Autor:
Al-Nabki, Mhd Wesam, Fidalgo, Eduardo, Vasco-Carofilis, Roberto A., Jañez-Martino, Francisco, Velasco-Mata, Javier
The information technology revolution has facilitated reaching pornographic material for everyone, including minors who are the most vulnerable in case they were abused. Accuracy and time performance are features desired by forensic tools oriented to
Externí odkaz:
http://arxiv.org/abs/2005.08766
Autor:
Al-Nabki, Mhd Wesam, Jañez-Martino, Francisco, Vasco-Carofilis, Roberto A., Fidalgo, Eduardo, Velasco-Mata, Javier
Name entity recognition in noisy user-generated texts is a difficult task usually enhanced by incorporating an external resource of information, such as gazetteers. However, gazetteers are task-specific, and they are expensive to build and maintain.
Externí odkaz:
http://arxiv.org/abs/2005.08746
Autor:
Jáñez-Martino, Francisco, Fidalgo, Eduardo, González-Martínez, Santiago, Velasco-Mata, Javier
Spammers take advantage of email popularity to send indiscriminately unsolicited emails. Although researchers and organizations continuously develop anti-spam filters based on binary classification, spammers bypass them through new strategies, like w
Externí odkaz:
http://arxiv.org/abs/2005.08773
Autor:
Velasco-Mata, Javier1,2 (AUTHOR) javier.velasco@unileon.es, González-Castro, Víctor1,2 (AUTHOR), Fidalgo, Eduardo1,2 (AUTHOR), Alegre, Enrique1,2 (AUTHOR)
Publikováno v:
Scientific Reports. 3/15/2023, Vol. 13 Issue 1, p1-10. 10p.
Autor:
Velasco Mata, Javier, Chaves, Deisy, Mata, Verónica de, Al-Nabki, Mhd Wesam, Fidalgo, Eduardo, Alegre, Enrique, Azzopardi, George
Face detection techniques are valuable in the forensic investigation since they help criminal investigators to identify victims/offenders in child sexual exploitation material. Deep learning approaches proved successful in these tasks, but their high
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1811::30a751faf22f974ba14db5e53a5e89d7
http://doi.org/10.18239/jornadas_2021.34.28
http://doi.org/10.18239/jornadas_2021.34.28
Autor:
Castaño, Felipe, Sánchez Paniagua, Manuel, Delgado Sotes, Juan José, Velasco Mata, Javier, Sepúlveda, Antonio, Fidalgo, Eduardo, Alegre, Enrique
Pphishing is one of the most common cyber-attacks.Machine Learning approaches can effectively deal with Phishing detection. However, models are trained on datasets with landing pages as legitimate samples without login forms, which is a situation clo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1811::b9446ee23e2f49e5dd19bed8e1b1fac9
http://doi.org/10.18239/jornadas_2021.34.06
http://doi.org/10.18239/jornadas_2021.34.06