Performance of Machine Learning-Based Multi-Model Voting Ensemble Methods for Network Threat Detection in Agriculture 4.0.

Peppes, Nikolaos; Daskalakis, Emmanouil; Alexakis, Theodoros; Adamopoulou, Evgenia; Demestichas, Konstantinos

Peppes, Nikolaos; Daskalakis, Emmanouil; Alexakis, Theodoros; Adamopoulou, Evgenia; Demestichas, Konstantinos.

Afiliación

Peppes N; Institute of Communication and Computer Systems, National Technical University of Athens, 15773 Athens, Greece.
Daskalakis E; Institute of Communication and Computer Systems, National Technical University of Athens, 15773 Athens, Greece.
Alexakis T; Institute of Communication and Computer Systems, National Technical University of Athens, 15773 Athens, Greece.
Adamopoulou E; Institute of Communication and Computer Systems, National Technical University of Athens, 15773 Athens, Greece.
Demestichas K; Institute of Communication and Computer Systems, National Technical University of Athens, 15773 Athens, Greece.

Sensors (Basel) ; 21(22)2021 Nov 10.

Article en En | MEDLINE | ID: mdl-34833551

Asunto(s)

Algoritmos; Aprendizaje Automático; Agricultura; Análisis por Conglomerados; Política

Palabras clave

Agriculture 4.0; active attacks; cybersecurity; e-Commerce; intrusion detection; machine learning; network security; network threats; network traffic classification; voting ensemble

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Aprendizaje Automático Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Sensors (Basel) Año: 2021 Tipo del documento: Article País de afiliación: Grecia Pais de publicación: Suiza

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