May 19, 2023, 1:10 a.m. | Soumyadeep Hore, Jalal Ghadermazi, Diwas Paudel, Ankit Shah, Tapas K. Das, Nathaniel D. Bastian

cs.CR updates on arXiv.org arxiv.org

Recent advancements in artificial intelligence (AI) and machine learning (ML)
algorithms, coupled with the availability of faster computing infrastructure,
have enhanced the security posture of cybersecurity operations centers
(defenders) through the development of ML-aided network intrusion detection
systems (NIDS). Concurrently, the abilities of adversaries to evade security
have also increased with the support of AI/ML models. Therefore, defenders need
to proactively prepare for evasion attacks that exploit the detection
mechanisms of NIDS. Recent studies have found that the perturbation of …

adversarial adversaries algorithms artificial artificial intelligence availability centers computing cybersecurity defenders detection development evade framework infrastructure intelligence intrusion intrusion detection machine machine learning network network packet operations packet posture security security posture systems

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