most citedHercules: Boosting the Performance of Privacy-preserving Federated Learning

1 citations · 2 across the 3 of their papers we have counts for

collaborators

3 papers

cs.CR2022★ 1 cited

Hercules: Boosting the Performance of Privacy-preserving Federated Learning

Guowen Xu, Xingshuo Han, Shengmin Xu +4

In this paper, we address the problem of privacy-preserving federated neural network training with users. We present Hercules, an efficient and high-precision training framewor…

cs.CR2022

A Secure Fingerprinting Framework for Distributed Image Classification

Guowen Xu, Xingshuo Han, Anguo Zhang +1

The deep learning (DL) technology has been widely used for image classification in many scenarios, e.g., face recognition and suspect tracking. Such a highly commercialized applica…

cs.CR2022★ 1 cited

SIMC 2.0: Improved Secure ML Inference Against Malicious Clients

Guowen Xu, Xingshuo Han, Tianwei Zhang +5

In this paper, we study the problem of secure ML inference against a malicious client and a semi-trusted server such that the client only learns the inference output while the serv…