Shuffle Model of Differential Privacy: Numerical Composition for Federated Learning
In decentralized scenarios without fully trustable parties (e.g., in mobile edge computing or IoT environments), the shuffle model has recently emerged as a promising paradigm for differentially private federated learning. Despite many efforts of privacy accounting for federated learning with many s...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-02-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/3/1595 |
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