IRAS-SDLC: Lifecycle Risk Aggregation for Secure AI-Augmented Software Assurance Under RMF and Zero Trust
Modern machine learning approaches for vulnerability detection achieve strong performance within specific datasets, yet their reliability degrades under domain shift, limiting their effectiveness for real-world secure software development lifecycle (SDLC) decision-making. In particular, probabilisti...
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| Principais autores: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
MDPI AG
2026-05-01
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| Series: | Systems |
| Assuntos: | |
| Acceso en liña: | https://www.mdpi.com/2079-8954/14/5/546 |
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