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Xiao-Yuan Yang

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PNFR: practicality-enhanced and non-interactive privacy-preserving federated regressions

PNFR is designed, a privacy-preserving federated learning scheme for regressions training built on the MPaillier algorithm, which is three times faster than interactive federated regressions PrivFL and about 80% faster than non-interactive federated regressions VANE.

Hui-Yu Xie, Tanping Zhou, Shuo Chen et al. · 0 citations
Open access Aug 2026

DMSA-FL: secure and robust federated learning via double-masked secure aggregation with multiparty homomorphic encryption

This paper proposes DMSA-FL as a practical and robust FL framework leveraging double-masked secure aggregation integrated with multiparty homomorphic encryption, and designs a strategy that encrypts only low-dimensional mask seeds rather than high-dimensional gradients.

Wen-Hao Liu, Xu-An Wang, Wei-Wei Jiang et al. · 0 citations

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