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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
Large Language Model (LLM) for Telecommunications: A Comprehensive Survey on Principles, Key Techniques, and Opportunities—0
Generic Multi-modal Representation Learning for Network Traffic Analysis—0
FedAuxHMTL: Federated Auxiliary Hard-Parameter Sharing Multi-Task Learning for Network Edge Traffic Classification—0
CBR - Boosting Adaptive Classification By Retrieval of Encrypted Network Traffic with Out-of-distribution—0
One Train for Two Tasks: An Encrypted Traffic Classification Framework Using Supervised Contrastive LearningCode2
Deep Learning Approaches for Network Traffic Classification in the Internet of Things (IoT): A Survey—0
Data Augmentation for Traffic Classification—0
From Classification to Optimization: Slicing and Resource Management with TRACTOR—0
DataZoo: Streamlining Traffic Classification ExperimentsCode1
netFound: Foundation Model for Network SecurityCode1
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