Introducing Perturb-ability Score (PS) to Enhance Robustness Against Evasion Adversarial Attacks on ML-NIDS

As network security threats continue to evolve, safeguarding Machine Learning (ML)-based Network Intrusion Detection Systems (NIDS) from adversarial attacks is crucial. This paper introduces the notion of feature perturb-ability and presents a novel Perturb-ability Score (PS) metric that identifies...

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Hauptverfasser:	elShehaby, Mohamed, Matrawy, Ashraf
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Artificial Intelligence Computer Science - Cryptography and Security Computer Science - Learning
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