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...
محفوظ في:
| المؤلفون الرئيسيون: | , , , |
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| التنسيق: | Artigo |
| اللغة: | Inglês |
| منشور في: |
SpringerOpen
2026-01-01
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| سلاسل: | Cybersecurity |
| الموضوعات: | |
| الوصول للمادة أونلاين: | https://doi.org/10.1186/s42400-025-00420-2 |
| الوسوم: |
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