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Traffic Classification

Traffic Classification is a task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Classification can be used for several purposes including policy enforcement and control or QoS management.

Source: Classification of Traffic Using Neural Networks by Rejecting: a Novel Approach in Classifying VPN Traffic

Papers

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Showing 1–10 of 110 papers

TitleStatusHype
One Train for Two Tasks: An Encrypted Traffic Classification Framework Using Supervised Contrastive LearningCode2
NetMamba: Efficient Network Traffic Classification via Pre-training Unidirectional MambaCode2
Revolutionizing Encrypted Traffic Classification with MH-Net: A Multi-View Heterogeneous Graph ModelCode2
TrafficGPT: An LLM Approach for Open-Set Encrypted Traffic ClassificationCode2
ET-BERT: A Contextualized Datagram Representation with Pre-training Transformers for Encrypted Traffic ClassificationCode2
MIETT: Multi-Instance Encrypted Traffic Transformer for Encrypted Traffic ClassificationCode1
MTC: A Multi-Task Model for Encrypted Network Traffic Classification Based on Transformer and 1D-CNNCode1
DataZoo: Streamlining Traffic Classification ExperimentsCode1
Deep Learning for Network Traffic ClassificationCode1
AutoML4ETC: Automated Neural Architecture Search for Real-World Encrypted Traffic ClassificationCode1
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