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Traffic Classification

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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

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/ArielCyber/When_a_RF_Beats_a_CNN_and_GRU

공식 코드

When a RF Beats a CNN and GRU, Together -- A Comparison of Deep Learning and Classical Machine Learning Approaches for Encrypted Malware Traffic Classification

https://github.com/CESNET/cesnet-models

공식 코드

Universal Embedding Function for Traffic Classification via QUIC Domain Recognition Pretraining: A Transfer Learning Success

https://github.com/JiahuiKChen/Practical-Configurable-Network-Traffic-Classification

공식 코드

Practical and Configurable Network Traffic Classification Using Probabilistic Machine Learning

https://github.com/Nirhoshan/NetDiffus

공식 코드

NetDiffus: Network Traffic Generation by Diffusion Models through Time-Series Imaging

https://github.com/SNL-UCSB/netFound

공식 코드

netFound: Foundation Model for Network Security

https://github.com/ViktorAxelsen/TFE-GNN

공식 코드

TFE-GNN: A Temporal Fusion Encoder Using Graph Neural Networks for Fine-grained Encrypted Traffic Classification

https://github.com/arielcyber/itc-data-augmentations-

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Enhancing Encrypted Internet Traffic Classification Through Advanced Data Augmentation Techniques

https://github.com/arielcyber/osf-eimtc

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Open-Source Framework for Encrypted Internet and Malicious Traffic Classification

https://github.com/brunabazaluk/tabtransformer_iot_attacks

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Towards a Transformer-Based Pre-trained Model for IoT Traffic Classification

https://github.com/cesnet/cesnet-datazoo

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DataZoo: Streamlining Traffic Classification Experiments

https://github.com/fkthi/OpenTrafficMonitoringPlus

공식 코드

Vehicle Position Estimation with Aerial Imagery from Unmanned Aerial Vehicles

https://github.com/flowfrontiers/autoflow

공식 코드

AutoFlow: An Autoencoder-based Approach for IP Flow Record Compression with Minimal Impact on Traffic Classification

https://github.com/ict-net/NetGPT

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NetGPT: Generative Pretrained Transformer for Network Traffic

https://github.com/koumajos/classification_by_nettisa_flow

공식 코드

NetTiSA: Extended IP Flow with Time-series Features for Universal Bandwidth-constrained High-speed Network Traffic Classification

https://github.com/koumajos/classificationbasedonsfts

공식 코드

Network Traffic Classification based on Single Flow Time Series Analysis

https://github.com/linwhitehat/et-bert

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ET-BERT: A Contextualized Datagram Representation with Pre-training Transformers for Encrypted Traffic Classification

https://github.com/niloofarbayat/NetworkClassification

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Deep Learning for Network Traffic Classification

https://github.com/orangeuw/automl4etc

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AutoML4ETC: Automated Neural Architecture Search for Real-World Encrypted Traffic Classification

https://github.com/secilia-cxy/miett

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MIETT: Multi-Instance Encrypted Traffic Transformer for Encrypted Traffic Classification

https://github.com/shrezaei/MultitaskTrafficClassification

공식 코드

Multitask Learning for Network Traffic Classification

https://github.com/tcbenchstack/tcbench

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Replication: Contrastive Learning and Data Augmentation in Traffic Classification Using a Flowpic Input Representation

https://github.com/viktoraxelsen/cle-tfe

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One Train for Two Tasks: An Encrypted Traffic Classification Framework Using Supervised Contrastive Learning

https://github.com/viktoraxelsen/mh-net

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Revolutionizing Encrypted Traffic Classification with MH-Net: A Multi-View Heterogeneous Graph Model

https://github.com/wangtz19/NetMamba

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NetMamba: Efficient Network Traffic Classification via Pre-training Unidirectional Mamba

https://github.com/xaiseries/lexnet

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A Lightweight, Efficient and Explainable-by-Design Convolutional Neural Network for Internet Traffic Classification

https://github.com/yoga-suhas-km/s2mc-for-cos

공식 코드

Segmented Learning for Class-of-Service Network Traffic Classification

https://github.com/KimythAnly/deeppacket

Deep Packet: A Novel Approach For Encrypted Traffic Classification Using Deep Learning

https://github.com/PrivPkt/PrivPkt

Deep Packet: A Novel Approach For Encrypted Traffic Classification Using Deep Learning

https://github.com/YuriBogdanov/DeepPacket

Deep Packet: A Novel Approach For Encrypted Traffic Classification Using Deep Learning

https://github.com/mhwong2007/Deep-Packet

Deep Packet: A Novel Approach For Encrypted Traffic Classification Using Deep Learning

https://github.com/mrazimi99/deep-packet

Deep Packet: A Novel Approach For Encrypted Traffic Classification Using Deep Learning

https://github.com/nura-j/attack_fl

Genetic Algorithm-Based Dynamic Backdoor Attack on Federated Learning-Based Network Traffic Classification

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