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A Network Intrusion Detection System (NIDS) that utilizes adversarial training to identify zero-day attacks and improve model robustness against malicious evasion attempts.
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With only 1 star and no forks after 19 days, this project is effectively a personal experiment or student project. It applies known adversarial ML techniques to the standard problem of network security, offering no significant moat or novel architectural breakthrough.
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