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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
ET-BERT: A Contextualized Datagram Representation with Pre-training Transformers for Encrypted Traffic ClassificationCode2
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
NetMamba: Efficient Network Traffic Classification via Pre-training Unidirectional MambaCode2
MIETT: Multi-Instance Encrypted Traffic Transformer for Encrypted Traffic ClassificationCode1
A Lightweight, Efficient and Explainable-by-Design Convolutional Neural Network for Internet Traffic ClassificationCode1
Replication: Contrastive Learning and Data Augmentation in Traffic Classification Using a Flowpic Input RepresentationCode1
Vehicle Position Estimation with Aerial Imagery from Unmanned Aerial VehiclesCode1
Privacy-preserving Few-shot Traffic Detection against Advanced Persistent Threats via Federated Meta LearningCode1
Deep Packet: A Novel Approach For Encrypted Traffic Classification Using Deep LearningCode1
Network Traffic Classification based on Single Flow Time Series AnalysisCode1
Deep Learning for Network Traffic ClassificationCode1
netFound: Foundation Model for Network SecurityCode1
Open-Source Framework for Encrypted Internet and Malicious Traffic ClassificationCode1
NetGPT: Generative Pretrained Transformer for Network TrafficCode1
MTC: A Multi-Task Model for Encrypted Network Traffic Classification Based on Transformer and 1D-CNNCode1
AutoML4ETC: Automated Neural Architecture Search for Real-World Encrypted Traffic ClassificationCode1
Universal Embedding Function for Traffic Classification via QUIC Domain Recognition Pretraining: A Transfer Learning SuccessCode1
DataZoo: Streamlining Traffic Classification ExperimentsCode1
NetDiffus: Network Traffic Generation by Diffusion Models through Time-Series ImagingCode1
TFE-GNN: A Temporal Fusion Encoder Using Graph Neural Networks for Fine-grained Encrypted Traffic ClassificationCode1
AutoFlow: An Autoencoder-based Approach for IP Flow Record Compression with Minimal Impact on Traffic ClassificationCode0
When a RF Beats a CNN and GRU, Together -- A Comparison of Deep Learning and Classical Machine Learning Approaches for Encrypted Malware Traffic ClassificationCode0
Genetic Algorithm-Based Dynamic Backdoor Attack on Federated Learning-Based Network Traffic ClassificationCode0
Towards a Transformer-Based Pre-trained Model for IoT Traffic ClassificationCode0
Segmented Learning for Class-of-Service Network Traffic ClassificationCode0
NetTiSA: Extended IP Flow with Time-series Features for Universal Bandwidth-constrained High-speed Network Traffic ClassificationCode0
Enhancing Encrypted Internet Traffic Classification Through Advanced Data Augmentation TechniquesCode0
Multitask Learning for Network Traffic ClassificationCode0
Practical and Configurable Network Traffic Classification Using Probabilistic Machine LearningCode0
Discern-XR: An Online Classifier for Metaverse Network Traffic—0
Development of Multistage Machine Learning Classifier using Decision Trees and Boosting Algorithms over Darknet Network Traffic—0
Augmentation Scheme for Dealing with Imbalanced Network Traffic Classification Using Deep Learning—0
Active Learning Framework to Automate NetworkTraffic Classification—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
Deep Learning and Traffic Classification: Lessons learned from a commercial-grade dataset with hundreds of encrypted and zero-day applications—0
Group & Reweight: A Novel Cost-Sensitive Approach to Mitigating Class Imbalance in Network Traffic Classification—0
Anomaly Detection Framework Using Rule Extraction for Efficient Intrusion Detection—0
Active Learning for Network Traffic Classification: A Technical Study—0
A Natural Language-Inspired Multi-label Video Streaming Traffic Classification Method Based on Deep Neural Networks—0
Generic Multi-modal Representation Learning for Network Traffic Analysis—0
Generative Adversarial Classification Network with Application to Network Traffic Classification—0
Data Augmentation for Traffic Classification—0
Flow-Packet Hybrid Traffic Classification for Class-Aware Network Routing—0
Federated Traffic Synthesizing and Classification Using Generative Adversarial Networks—0
Heterogeneous Data-Aware Federated Learning—0
Darknet Traffic Classification and Adversarial Attacks—0
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