Skip to content

Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness (IJCAI'19).

Notifications You must be signed in to change notification settings

haiphanNJIT/SecureSGD

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

14 Commits
 
 
 
 
 
 

Repository files navigation

SecureSGD

These are the codes used in the paper titled: "Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness." (https://128.84.21.199/pdf/1906.01444.pdf) The 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), August 10-16, 2019, Macao, China. (acceptance rate = 850/4752, 17.9%)

Requirement

The software is written in tensorflow. It requires the following packages: python3, Tensorflow 1.1 or later.

If you use this code, please cite our paper.

About

Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness (IJCAI'19).

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages