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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
Deep Learning and Traffic Classification: Lessons learned from a commercial-grade dataset with hundreds of encrypted and zero-day applications—0
Anomaly Detection Framework Using Rule Extraction for Efficient Intrusion Detection—0
Active Learning for Network Traffic Classification: A Technical Study—0
The Adversarial Machine Learning Conundrum: Can The Insecurity of ML Become The Achilles' Heel of Cognitive Networks?—0
Data Augmentation for Traffic Classification—0
Darknet Traffic Classification and Adversarial Attacks—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
Malicious Requests Detection with Improved Bidirectional Long Short-term Memory Neural Networks—0
Energy-Efficient Deep Learning for Traffic Classification on Microcontrollers—0
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