302 citations · 547 across the 18 of their papers we have counts for
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cs.CR2019★ 302 cited
HybridAlpha: An Efficient Approach for Privacy-Preserving Federated Learning
Runhua Xu, Nathalie Baracaldo, Yi Zhou +2
Federated learning has emerged as a promising approach for collaborative and privacy-preserving learning. Participants in a federated learning process cooperatively train a model b…
cs.CR2019★ 9 cited
CryptoNN: Training Neural Networks over Encrypted Data
Runhua Xu, James B. D. Joshi, Chao Li
Emerging neural networks based machine learning techniques such as deep learning and its variants have shown tremendous potential in many application domains. However, they raise s…
cs.CR2019★ 10 cited
Scalable and Privacy-preserving Design of On/Off-chain Smart Contracts
Chao Li, Balaji Palanisamy, Runhua Xu
The rise of smart contract systems such as Ethereum has resulted in a proliferation of blockchain-based decentralized applications including applications that store and manage a wi…