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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 51–60 of 110 papers

TitleStatusHype
Malware Traffic Classification: Evaluation of Algorithms and an Automated Ground-truth Generation Pipeline—0
Many or Few Samples? Comparing Transfer, Contrastive and Meta-Learning in Encrypted Traffic Classification—0
MERLOT: A Distilled LLM-based Mixture-of-Experts Framework for Scalable Encrypted Traffic Classification—0
Multi-view Multi-label Anomaly Network Traffic Classification based on MLP-Mixer Neural Network—0
Net2Vec: Deep Learning for the Network—0
NetFlowGen: Leveraging Generative Pre-training for Network Traffic Dynamics—0
Network Traffic Anomaly Detection Method Based on Multi scale Residual Feature—0
Network Traffic Classification Using Machine Learning, Transformer, and Large Language Models—0
Non-uniformity is All You Need: Efficient and Timely Encrypted Traffic Classification With ECHO—0
OMINACS: Online ML-Based IoT Network Attack Detection and Classification System—0
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