Clique-based multi-class oversampling with central and boundary instance strategies for intrusion detection

Abstract Intrusion detection systems are essential for maintaining network security, yet they often face severe class imbalance, especially in multi-class intrusion scenarios, which leads to biased learning and poor recognition of minority attacks. Traditional oversampling methods, such as SMOTE and...

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Hlavní autoři:	Hui Xu, Ji-ming Gong, Long-hui Wang
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Springer 2026-05-01
Edice:	Discover Artificial Intelligence
Témata:	Intrusion detection system Multi-class classification Maximal cliques Cosine similarity Radial interpolation Oversampling
On-line přístup:	https://doi.org/10.1007/s44163-026-01338-5
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