flowRecorder - a network traffic flow feature measurement tool
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Updated
Jan 14, 2019 - Python
flowRecorder - a network traffic flow feature measurement tool
Using SIFT features, BOW, model: SVM
Use deep learning to classify the malicious traffic, and use TensorFlow2.0 to carry out it.
🐳📡🐶 Generate network communication data for target tasks in diverse network conditions.
Deep Learning models for network traffic classification
Network Measurement Lab course homeworks - 2021/2022
Pytorch implementation of deep packet: a novel approach for encrypted traffic classification using deep learning
Privacy Preserving Collaborative Encrypted Network Traffic Classification (Differential Privacy, Federated Learning, Membership Inference Attack, Encrypted Traffic Classification)
A repository with models for encrypted traffic classification.
This is a beginner's coursework about Net traffic classification using ML
tcbench is a Machine Learning and Deep Learning framework to train model from traffic packet time series or other input representations.
A web-based solution utilizing a robust tensorflow model for precise traffic condition classification made in ReactJs and FastAPI for backend.
Toolkit for processing PCAP file and transform into image of MNIST dataset
In this paper, we proposed a deep learning model which achieves progress compared to LeNet-5 in the stability of Internet traffic classification.
AutoML4ETC, a tool to automatically design efficient and high-performing neural architectures for encrypted traffic classification.
Mobile Traffic Classification using Deep Learning
Traffic Fingerprinting using Autoencoders
一个流量分类的封装框架
pcap file analysis, only deal with ipV4
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