Traffic Fingerprinting using Autoencoders
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Updated
Mar 5, 2024 - Python
Traffic Fingerprinting using Autoencoders
This is a beginner's coursework about Net traffic classification using ML
A repository with models for encrypted traffic classification.
pcap file analysis, only deal with ipV4
NetFlow aggregation and graph toolkit
Mobile Traffic Classification using Deep Learning
Network Measurement Lab course homeworks - 2021/2022
In this paper, we proposed a deep learning model which achieves progress compared to LeNet-5 in the stability of Internet traffic classification.
🐳📡🐶 Generate network communication data for target tasks in diverse network conditions.
A web-based solution utilizing a robust tensorflow model for precise traffic condition classification made in ReactJs and FastAPI for backend.
Jupyter notebooks with traffic classification examples using CESNET DataZoo and CESNET Models packages
CESNET Models: Neural networks for network traffic classification
AutoML4ETC, a tool to automatically design efficient and high-performing neural architectures for encrypted traffic classification.
flowRecorder - a network traffic flow feature measurement tool
CESNET DataZoo: A toolset for large network traffic datasets
Using SIFT features, BOW, model: SVM
tcbench is a Machine Learning and Deep Learning framework to train model from traffic packet time series or other input representations.
一个流量分类的封装框架
Use deep learning to classify the malicious traffic, and use TensorFlow2.0 to carry out it.
Efficient Network Traffic Classification via Pre-training Unidirectional Mamba
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