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.
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
.
DOI: 10.3969/j.issn.0255-8297.2023.04.009
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