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Accessibility of covariance information creates vulnerability in Federated Learning frameworks
MOTIVATION: Federated Learning (FL) is gaining traction in various fields as it enables integrative data analysis without sharing sensitive data, such as in healthcare. However, the risk of data leakage caused by malicious attacks must be considered. In this study, we introduce a novel attack algori...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10516515/ https://www.ncbi.nlm.nih.gov/pubmed/37647639 http://dx.doi.org/10.1093/bioinformatics/btad531 |