Traffic Fingerprinting using Autoencoders
-
Updated
Mar 5, 2024 - Python
Traffic Fingerprinting using Autoencoders
pcap file analysis, only deal with ipV4
This is a beginner's coursework about Net traffic classification using ML
A repository with models for encrypted traffic classification.
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.
CESNET Models: Neural networks for network traffic classification
Jupyter notebooks with traffic classification examples using CESNET DataZoo and CESNET Models packages
AutoML4ETC, a tool to automatically design efficient and high-performing neural architectures for encrypted traffic classification.
CESNET DataZoo: A toolset for large network traffic datasets
flowRecorder - a network traffic flow feature measurement tool
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
Efficient Network Traffic Classification via Pre-training Unidirectional Mamba
Use deep learning to classify the malicious traffic, and use TensorFlow2.0 to carry out it.
Add a description, image, and links to the traffic-classification topic page so that developers can more easily learn about it.
To associate your repository with the traffic-classification topic, visit your repo's landing page and select "manage topics."