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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 71–80 of 110 papers

TitleStatusHype
Active Learning for Network Traffic Classification: A Technical Study—0
Active Learning Framework to Automate NetworkTraffic Classification—0
A First Look at Class Incremental Learning in Deep Learning Mobile Traffic Classification—0
A General Approach for Traffic Classification in Wireless Networks Using Deep Learning—0
Malicious Requests Detection with Improved Bidirectional Long Short-term Memory Neural Networks—0
Anomaly Detection Framework Using Rule Extraction for Efficient Intrusion Detection—0
Applications of Artificial Intelligence, Machine Learning and related techniques for Computer Networking Systems—0
Augmentation Scheme for Dealing with Imbalanced Network Traffic Classification Using Deep Learning—0
CBR - Boosting Adaptive Classification By Retrieval of Encrypted Network Traffic with Out-of-distribution—0
CGNN: Traffic Classification with Graph Neural Network—0
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