Jun 27, 2024 · To protect data privacy, a promising way is to exploit various types of secret sharing to implement privacy-preserving neural network inference.

To address this issue, we proposed Cenia, a communication- efficient privacy-preserving neural network inference scheme purely via arithmetic secret sharing.

Oct 22, 2024 · In this paper, we leverage the lightweight arithmetic secret sharing to develop a new communication-efficient privacy-preserving neural network ...

1 day ago · To protect data privacy, a promising way is to exploit various types of secret sharing to implement privacy-preserving neural network inference.

We reduce communication costs in the online and offline phases by combining additive secret sharing and function secret sharing, and replace the trusted dealer ...

Article "Communication-Efficient Privacy-Preserving Neural Network Inference via Arithmetic Secret Sharing" Detailed information of the J-GLOBAL is an ...

To summarize, distributed training raises two kinds of concerns: (i) security of one party's data against other parties during training and (ii) privacy leakage ...

In this work, we design and implement new privacy-preserving machine learning protocols for logistic regression and neural network models. We adopt a two-server ...

Abstract: We propose AriaNN, a low-interaction privacy-preserving framework for private neural network training and inference on sensitive data.

Oct 19, 2024 · We propose a privacy-preserving and verifiable scheme for convolutional neural network inference and training in cloud computing.