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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 51–75 of 110 papers

TitleStatusHype
TFE-GNN: A Temporal Fusion Encoder Using Graph Neural Networks for Fine-grained Encrypted Traffic ClassificationCode1
Network Traffic Classification based on Single Flow Time Series AnalysisCode1
Real-time Traffic Classification for 5G NSA Encrypted Data Flows With Physical Channel Records—0
Many or Few Samples? Comparing Transfer, Contrastive and Meta-Learning in Encrypted Traffic Classification—0
MTC: A Multi-Task Model for Encrypted Network Traffic Classification Based on Transformer and 1D-CNNCode1
NetGPT: Generative Pretrained Transformer for Network TrafficCode1
On the Local Cache Update Rules in Streaming Federated Learning—0
Generative Adversarial Classification Network with Application to Network Traffic Classification—0
OMINACS: Online ML-Based IoT Network Attack Detection and Classification System—0
Multi-view Multi-label Anomaly Network Traffic Classification based on MLP-Mixer Neural Network—0
Active Learning Framework to Automate NetworkTraffic Classification—0
To Store or Not? Online Data Selection for Federated Learning with Limited Storage—0
Traffic Analytics Development Kits (TADK): Enable Real-Time AI Inference in Networking Apps—0
Segmented Learning for Class-of-Service Network Traffic ClassificationCode0
Open-Source Framework for Encrypted Internet and Malicious Traffic ClassificationCode1
When a RF Beats a CNN and GRU, Together -- A Comparison of Deep Learning and Classical Machine Learning Approaches for Encrypted Malware Traffic ClassificationCode0
Darknet Traffic Classification and Adversarial Attacks—0
Network Traffic Anomaly Detection Method Based on Multi scale Residual Feature—0
Federated Semi-Supervised Classification of Multimedia Flows for 3D Networks—0
Deep Learning for Encrypted Traffic Classification and Unknown Data Detection—0
A General Approach for Traffic Classification in Wireless Networks Using Deep Learning—0
ET-BERT: A Contextualized Datagram Representation with Pre-training Transformers for Encrypted Traffic ClassificationCode2
A Lightweight, Efficient and Explainable-by-Design Convolutional Neural Network for Internet Traffic ClassificationCode1
CGNN: Traffic Classification with Graph Neural Network—0
Time-Distributed Feature Learning in Network Traffic Classification for Internet of Things—0
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