Heterogeneous federated learning for imbalanced phishing email detection

Abstract Phishing email attacks have evolved into a significant threat, causing substantial economic and political harm. However, existing detection methods often neglect the data heterogeneity resulting from diverse email sources and are trained on balanced email datasets, which do not accurately r...

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Hlavní autoři:	Xiaoyang Yi, Linyu Li, Jian Zhang, Zedong Jia
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	SpringerOpen 2026-01-01
Edice:	Cybersecurity
Témata:	Federated learning Phishing email detection Class imbalance
On-line přístup:	https://doi.org/10.1186/s42400-025-00420-2
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