Deep Ensemble Learning for Application Traffic Classification Using Differential Model Selection Technique

Deep Ensemble Learning for Application Traffic Classification Using Differential Model Selection Technique

As the Internet evolves, application traffic is becoming increasingly diverse and complex, leading network administrators to demand more accurate application traffic classification. Various deep learning-based application traffic classification methods have clearly achieved significant success, demo...

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Bibliographic Details
Main Authors: Ui-Jun Baek, Yoon-Seong Jang, Ju-Sung Kim, Yang-Seo Choi, Myung-Sup Kim
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Sensors
Subjects:
deep ensemble
model selection technique
application traffic classification
end-to-end ensemble learning
network management
Online Access:https://www.mdpi.com/1424-8220/25/9/2853
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