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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 21–30 of 110 papers

TitleStatusHype
AutoFlow: An Autoencoder-based Approach for IP Flow Record Compression with Minimal Impact on Traffic ClassificationCode0
Towards a graph-based foundation model for network traffic analysis—0
Time-Distributed Feature Learning for Internet of Things Network Traffic Classification—0
TrafficGPT: An LLM Approach for Open-Set Encrypted Traffic ClassificationCode2
Efficiently and Effectively: A Two-stage Approach to Balance Plaintext and Encrypted Text for Traffic Classification—0
Towards a Transformer-Based Pre-trained Model for IoT Traffic ClassificationCode0
Enhancing Encrypted Internet Traffic Classification Through Advanced Data Augmentation TechniquesCode0
Development of Multistage Machine Learning Classifier using Decision Trees and Boosting Algorithms over Darknet Network Traffic—0
Non-uniformity is All You Need: Efficient and Timely Encrypted Traffic Classification With ECHO—0
NetMamba: Efficient Network Traffic Classification via Pre-training Unidirectional MambaCode2
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