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.

Afiliação

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 em En | MEDLINE | ID: mdl-34833551

Assuntos

Algoritmos; Aprendizado de Máquina; Agricultura; Análise por Conglomerados; Política

Palavras-chave

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 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Aprendizado de Máquina Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Grécia País de publicação: Suíça

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