BFSN: A Novel Method of Encrypted Traffic Classification Based on Bidirectional Flow Sequence Network
Author:
Affiliation:
1. University of Science and Technology of China,Department of Cyberspace Security
2. University of Science and Technology of China,School of Information Science and Technology,Department of Automation
Funder
National Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9350667/9350740/09350824.pdf?arnumber=9350824
Cited by 8 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. A novel and effective encrypted traffic classification method based on channel attention and deformable convolution;Computers and Electrical Engineering;2024-08
2. Network Traffic Classification Model Based on Spatio-Temporal Feature Extraction;Electronics;2024-03-27
3. FastDet: Detecting Encrypted Malicious Traffic Faster via Early Exit;Lecture Notes in Computer Science;2024
4. An Effective Real-time Traffic Classification Method Using Convolutional Neural Network;2023-08-08
5. CMTSNN: A Deep Learning Model for Multiclassification of Abnormal and Encrypted Traffic of Internet of Things;IEEE Internet of Things Journal;2023-07-01
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