The authors define dynamic noisy multi-client functional encryption, present the PRF-based inner-product scheme DyNo, and use it to train a differentially private logistic regression with claimed millisecond-level performance.
In: Theory of Cryptography Conference
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CR 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Enhancing Noisy Functional Encryption for Privacy-Preserving Machine Learning
The authors define dynamic noisy multi-client functional encryption, present the PRF-based inner-product scheme DyNo, and use it to train a differentially private logistic regression with claimed millisecond-level performance.