jinminhao/PANTS
[Usenix Security '25] Robustifying ML-powered Network Classifiers with PANTS
This project helps network operators test and strengthen their machine learning models used for network traffic classification. It takes your existing network traffic classifier and identifies subtle changes to network data that could trick it, then helps retrain the model to be more resilient. The end user is a network operator or security engineer responsible for maintaining robust and secure network operations.
No commits in the last 6 months.
Use this if you need to assess and improve the reliability of your ML-powered network traffic classifiers against sophisticated, targeted attacks that could disrupt services or compromise security.
Not ideal if you are looking for a general-purpose adversarial machine learning tool outside of network traffic classification or if you do not have strong CPU resources available for evaluation.
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20
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3
Language
Python
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Category
Last pushed
Aug 16, 2025
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