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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 26–50 of 110 papers

TitleStatusHype
Deep Learning for Encrypted Traffic Classification and Unknown Data Detection—0
Deep Learning Approaches for Network Traffic Classification in the Internet of Things (IoT): A Survey—0
Applications of Artificial Intelligence, Machine Learning and related techniques for Computer Networking Systems—0
Development of Multistage Machine Learning Classifier using Decision Trees and Boosting Algorithms over Darknet Network Traffic—0
Discern-XR: An Online Classifier for Metaverse Network Traffic—0
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
MER-SDN: Machine Learning Framework for Traffic Aware Energy Efficient Routing in SDN—0
Data Augmentation for Traffic Classification—0
Federated Traffic Synthesizing and Classification Using Generative Adversarial Networks—0
Darknet Traffic Classification and Adversarial Attacks—0
Federated Semi-Supervised Classification of Multimedia Flows for 3D Networks—0
FedEdge AI-TC: A Semi-supervised Traffic Classification Method based on Trusted Federated Deep Learning for Mobile Edge Computing—0
FedAuxHMTL: Federated Auxiliary Hard-Parameter Sharing Multi-Task Learning for Network Edge Traffic Classification—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
Flow-Packet Hybrid Traffic Classification for Class-Aware Network Routing—0
Generative Adversarial Classification Network with Application to Network Traffic Classification—0
Generic Multi-modal Representation Learning for Network Traffic Analysis—0
Malicious Requests Detection with Improved Bidirectional Long Short-term Memory Neural Networks—0
Group & Reweight: A Novel Cost-Sensitive Approach to Mitigating Class Imbalance in Network Traffic Classification—0
Heterogeneous Data-Aware Federated Learning—0
Energy-Efficient Deep Learning for Traffic Classification on Microcontrollers—0
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