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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 31–40 of 110 papers

TitleStatusHype
PacketCLIP: Multi-Modal Embedding of Network Traffic and Language for Cybersecurity Reasoning—0
Network Traffic Classification Using Machine Learning, Transformer, and Large Language Models—0
NetFlowGen: Leveraging Generative Pre-training for Network Traffic Dynamics—0
VINEVI: A Virtualized Network Vision Architecture for Smart Monitoring of Heterogeneous Applications and Infrastructures—0
Improving the network traffic classification using the Packet Vision approach—0
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
AutoFlow: An Autoencoder-based Approach for IP Flow Record Compression with Minimal Impact on Traffic ClassificationCode0
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