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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 11–20 of 110 papers

TitleStatusHype
Universal Embedding Function for Traffic Classification via QUIC Domain Recognition Pretraining: A Transfer Learning SuccessCode1
Revolutionizing Encrypted Traffic Classification with MH-Net: A Multi-View Heterogeneous Graph ModelCode2
NetFlowGen: Leveraging Generative Pre-training for Network Traffic Dynamics—0
Improving the network traffic classification using the Packet Vision approach—0
VINEVI: A Virtualized Network Vision Architecture for Smart Monitoring of Heterogeneous Applications and Infrastructures—0
MIETT: Multi-Instance Encrypted Traffic Transformer for Encrypted Traffic ClassificationCode1
MERLOT: A Distilled LLM-based Mixture-of-Experts Framework for Scalable Encrypted Traffic Classification—0
Discern-XR: An Online Classifier for Metaverse Network Traffic—0
Group & Reweight: A Novel Cost-Sensitive Approach to Mitigating Class Imbalance in Network Traffic Classification—0
Packet Inspection Transformer: A Self-Supervised Journey to Unseen Malware Detection with Few Samples—0
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