A novel and effective encrypted traffic classification method based on channel attention and deformable convolution-Reference-Cited by-同舟云学术

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A novel and effective encrypted traffic classification method based on channel attention and deformable convolution

Published:2024-08 Issue: Volume:118 Page:109406
ISSN:0045-7906
Container-title:Computers and Electrical Engineering
language:en
Short-container-title:Computers and Electrical Engineering

Author:

Zou Aobo^ORCID,Yang Wen,Tang Chaowei,Lu Jingwen,Guo Jiayuan

Publisher

Elsevier BV

Reference33 articles.

1. Deep learning for encrypted traffic classification: an overview;Rezaei;IEEE Commun Mag,2019

2. High utility periodic frequent pattern mining in multiple sequences;Chen;Comput Model Eng Sci,2023

3. A survey on encrypted network traffic analysis applications, techniques, and countermeasures;Papadogiannaki;ACM Comput Surv,2022

4. Issues and future directions in traffic classification;Dainotti;IEEE Netw,2012

5. CETAnalytics: Comprehensive effective traffic information analytics for encrypted traffic classification;Dong;Comput Netw,2020

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