AriaNN: Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing
We propose AriaNN, a low-interaction privacy-preserving framework for private neural network training and inference on sensitive data.
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| Auteurs principaux: | , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Sciendo
2022
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/5d826b5e3d9b49df9f7ebc14cb47bd78 |
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| Résumé: | We propose AriaNN, a low-interaction privacy-preserving framework for private neural network training and inference on sensitive data. |
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