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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 1–50 of 110 papers

TitleStatusHype
NetMamba: Efficient Network Traffic Classification via Pre-training Unidirectional MambaCode2
Revolutionizing Encrypted Traffic Classification with MH-Net: A Multi-View Heterogeneous Graph ModelCode2
TrafficGPT: An LLM Approach for Open-Set Encrypted Traffic ClassificationCode2
One Train for Two Tasks: An Encrypted Traffic Classification Framework Using Supervised Contrastive LearningCode2
ET-BERT: A Contextualized Datagram Representation with Pre-training Transformers for Encrypted Traffic ClassificationCode2
netFound: Foundation Model for Network SecurityCode1
NetDiffus: Network Traffic Generation by Diffusion Models through Time-Series ImagingCode1
Deep Learning for Network Traffic ClassificationCode1
Privacy-preserving Few-shot Traffic Detection against Advanced Persistent Threats via Federated Meta LearningCode1
DataZoo: Streamlining Traffic Classification ExperimentsCode1
Replication: Contrastive Learning and Data Augmentation in Traffic Classification Using a Flowpic Input RepresentationCode1
Deep Packet: A Novel Approach For Encrypted Traffic Classification Using Deep LearningCode1
TFE-GNN: A Temporal Fusion Encoder Using Graph Neural Networks for Fine-grained Encrypted Traffic ClassificationCode1
NetGPT: Generative Pretrained Transformer for Network TrafficCode1
MIETT: Multi-Instance Encrypted Traffic Transformer for Encrypted Traffic ClassificationCode1
AutoML4ETC: Automated Neural Architecture Search for Real-World Encrypted Traffic ClassificationCode1
Network Traffic Classification based on Single Flow Time Series AnalysisCode1
Open-Source Framework for Encrypted Internet and Malicious Traffic ClassificationCode1
MTC: A Multi-Task Model for Encrypted Network Traffic Classification Based on Transformer and 1D-CNNCode1
A Lightweight, Efficient and Explainable-by-Design Convolutional Neural Network for Internet Traffic ClassificationCode1
Vehicle Position Estimation with Aerial Imagery from Unmanned Aerial VehiclesCode1
Universal Embedding Function for Traffic Classification via QUIC Domain Recognition Pretraining: A Transfer Learning SuccessCode1
Active Learning Framework to Automate NetworkTraffic Classification—0
Augmentation Scheme for Dealing with Imbalanced Network Traffic Classification Using Deep Learning—0
A Natural Language-Inspired Multi-label Video Streaming Traffic Classification Method Based on Deep Neural Networks—0
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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