Deep Learning models for network traffic classification
A New version of Python3 botnet, old version: http://github.com/Leeon123/Python3-botnet
Privacy Preserving Collaborative Encrypted Network Traffic Classification (Differential Privacy, Federated Learning, Membership Inference Attack, Encrypted Traffic Classification)
CESNET DataZoo: A toolset for large network traffic datasets
CESNET Models: Neural networks for network traffic classification
Jupyter notebooks with traffic classification examples using CESNET DataZoo and CESNET Models packages
This project integrates Explainable AI (XAI) techniques for anomaly detection in encrypted network traffic using ML Algorithms. We employ SHAP (SHapley Additive Explanations) to interpret model decisions and enhance transparency in detecting malicious activities. The system is designed to identify suspicious patterns in encrypted traffic.
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