TA-GAN: GAN based Traffic Augmentation for Imbalanced Network Traffic Classification-Reference-Cited by-同舟云学术

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TA-GAN: GAN based Traffic Augmentation for Imbalanced Network Traffic Classification

Published:2021-07-18 Issue: Volume: Page:
ISSN:
Container-title:2021 International Joint Conference on Neural Networks (IJCNN)
language:
Short-container-title:

Author:

Guo Yu,Xiong Gang,Li Zhen,Shi Junzheng,Cui Mingxin,Gou Gaopeng

Funder

The National Key Research and Development Program of China

Key Research and Development Program for Guangdong Province

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9533266/9533267/09533942.pdf?arnumber=9533942

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. CETP: A novel semi-supervised framework based on contrastive pre-training for imbalanced encrypted traffic classification;Computers & Security;2024-08

2. A Knowledge Distillation-Driven Lightweight CNN Model for Detecting Malicious Encrypted Network Traffic;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

3. MFL-RAT: Multi-class Few-Shot Learning Method for Encrypted RAT Traffic Detection;Lecture Notes in Computer Science;2024

4. NFlowGAN: High-Utility Privacy-Preserving Network Flow Synthesis Based on GAN;ICC 2023 - IEEE International Conference on Communications;2023-05-28

5. Examination of QUIC-based Website Fingerprinting;2022 6th International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS);2022-12-21

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