基于VPN通道下的加密流量分类算法

doi:10.3969/j.issn.0255-8297.2023.04.009

应用科学学报 ›› 2023, Vol. 41 ›› Issue (4): 646-656.doi: 10.3969/j.issn.0255-8297.2023.04.009

基于VPN通道下的加密流量分类算法

魏洁玲, 马秀丽, 金彦亮, 王瑞

上海大学通信与信息工程学院, 上海 200444

收稿日期:2021-09-22 发布日期:2023-08-02
通信作者: 马秀丽,副教授,研究方向为大数据和智能信息处理。E-mail:xlma@shu.edu.cn E-mail:xlma@shu.edu.cn
基金资助:
国家自然科学基金（No. 61771299）资助

Encrypted Traffic Classification Algorithm Based on VPN Channel

WEI Jieling, MA Xiuli, JIN Yanliang, WANG Rui

School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China

Received:2021-09-22 Published:2023-08-02

摘要/Abstract

摘要： 为了改善网络管理水平、加强网络安全监督，针对虚拟专用网络（virtual privatenetwork,VPN）通道下流量加密性强、不透明度高的特点，设计了加密流量数据的新构图方式，提出了基于变体ResNet18网络的加密流量分类算法。为了验证算法有效性，采集真实VPN通道下的热门app流量，成功实现了多VPN通道下的多应用流量分类。所提算法最终在公有数据集与真实采集数据集上的分类准确率分别达到98.1%和96.0%。实验结果表明，该算法具有通用性且具有一定的实际价值。

关键词: 深度学习, 加密流量, 虚拟专用网络, 残差网络

Abstract: This paper proposes a new encrypted traffic classification algorithm based on a variant ResNet18 network to improve network management and strengthen network security supervision. A three-channel image construction is designed to address the strong encryption and high opacity characteristics of traffic in virtual private network (VPN) channels. The proposed method successfully identifies different apps’ traffic in different VPN channels, as validated using popular apps’ traffic collected from real VPN channels. The algorithm achieves 98.1% and 96.0% classification accuracy on public and self-collected datasets, respectively. Experimental results demonstrate the algorithm’s universality and practical value.

Key words: deep learning, encrypted traffic, virtual private network (VPN), residual network

中图分类号:

TP309

魏洁玲, 马秀丽, 金彦亮, 王瑞. 基于VPN通道下的加密流量分类算法[J]. 应用科学学报, 2023, 41(4): 646-656.

WEI Jieling, MA Xiuli, JIN Yanliang, WANG Rui. Encrypted Traffic Classification Algorithm Based on VPN Channel[J]. Journal of Applied Sciences, 2023, 41(4): 646-656.

参考文献

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基于VPN通道下的加密流量分类算法

Encrypted Traffic Classification Algorithm Based on VPN Channel

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