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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 41–50 of 110 papers

TitleStatusHype
FedAuxHMTL: Federated Auxiliary Hard-Parameter Sharing Multi-Task Learning for Network Edge Traffic Classification—0
FastFlow: Early Yet Robust Network Flow Classification using the Minimal Number of Time-Series Packets—0
Classification of Traffic Using Neural Networks by Rejecting: a Novel Approach in Classifying VPN Traffic—0
Flow-Packet Hybrid Traffic Classification for Class-Aware Network Routing—0
Generative Adversarial Classification Network with Application to Network Traffic Classification—0
Generic Multi-modal Representation Learning for Network Traffic Analysis—0
Malicious Requests Detection with Improved Bidirectional Long Short-term Memory Neural Networks—0
Group & Reweight: A Novel Cost-Sensitive Approach to Mitigating Class Imbalance in Network Traffic Classification—0
Heterogeneous Data-Aware Federated Learning—0
Energy-Efficient Deep Learning for Traffic Classification on Microcontrollers—0
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