3 papers
cs.LG2020
S3ML: A Secure Serving System for Machine Learning Inference
Junming Ma, Chaofan Yu, Aihui Zhou +6
We present S3ML, a secure serving system for machine learning inference in this paper. S3ML runs machine learning models in Intel SGX enclaves to protect users' privacy. S3ML desig…
cs.CR2020
When Homomorphic Encryption Marries Secret Sharing: Secure Large-Scale Sparse Logistic Regression and Applications in Risk Control
Chaochao Chen, Jun Zhou, Li Wang +7
Logistic Regression (LR) is the most widely used machine learning model in industry for its efficiency, robustness, and interpretability. Due to the problem of data isolation and t…
cs.LG2020
Industrial Scale Privacy Preserving Deep Neural Network
Longfei Zheng, Chaochao Chen, Yingting Liu +6
Deep Neural Network (DNN) has been showing great potential in kinds of real-world applications such as fraud detection and distress prediction. Meanwhile, data isolation has become…