Review and Perspective on Encrypted Traffic Classification Based on Contrastive Learning-Reference-Cited by-同舟云学术

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Review and Perspective on Encrypted Traffic Classification Based on Contrastive Learning

Published:2024-04-12 Issue: Volume:33 Page:208-212
ISSN:
Container-title:2024 5th International Conference on Computer Engineering and Application (ICCEA)
language:
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Author:

Li Zhaodi¹,Liu Qingqing²,Yu Kaixuan³

Affiliation:

1. Henan University,Department of Computer and Information Engineering,Kaifeng,China

2. Henan Light Industry Vocational College,Department of Computer Science and Art,ZhengZhou,China

3. State Key Laboratory of Shield Machine and Boring Technology,ZhengZhou,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10603447/10603450/10604038.pdf?arnumber=10604038

Reference20 articles.

1. Deep packet: a novel approach for encrypted traffic classification using deep learning

2. FlowPrint: Semi-Supervised Mobile-App Fingerprinting on Encrypted Network Traffic

3. Network traffic classification for data fusion: A survey

4. FLAGB: Focal Loss based Adaptive Gradient Boosting for Imbalanced Traffic Classification

5. An effective convolutional neural network based on SMOTE and Gaussian mixture model for intrusion detection in imbalanced dataset

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