conference-paper

LWLC-CNN: Ultra-lightweight Network Traffic Classification Algorithm

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Abstract

With the diversification of 5G networks, the accurate classification of network traffic is of great significance to network management and optimization. Based on the study of classical volumes and neural networks, this paper proposes a lightweight, low convolutional neural network traffic classification algorithm-LWLC-CNN, to complete network traffic classification. Experimental results show that the proposed algorithm significantly reduces the computer's training capacity and model size, and has a good effect on network traffic classification.

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DOI
10.1109/indin58382.2024.10774251
OpenAlex
W4405305129
Document type
conference-paper
Language
EN
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