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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
Replication: Contrastive Learning and Data Augmentation in Traffic Classification Using a Flowpic Input RepresentationCode1
Privacy-preserving Few-shot Traffic Detection against Advanced Persistent Threats via Federated Meta LearningCode1
AutoML4ETC: Automated Neural Architecture Search for Real-World Encrypted Traffic ClassificationCode1
TFE-GNN: A Temporal Fusion Encoder Using Graph Neural Networks for Fine-grained Encrypted Traffic ClassificationCode1
Network Traffic Classification based on Single Flow Time Series AnalysisCode1
MTC: A Multi-Task Model for Encrypted Network Traffic Classification Based on Transformer and 1D-CNNCode1
NetGPT: Generative Pretrained Transformer for Network TrafficCode1
Open-Source Framework for Encrypted Internet and Malicious Traffic ClassificationCode1
A Lightweight, Efficient and Explainable-by-Design Convolutional Neural Network for Internet Traffic ClassificationCode1
Deep Learning for Network Traffic ClassificationCode1
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