IDASH2017 is a project for implementing our Logistic Regression Traning on encrypted datasets (Privacy-Preserving Logistic Regression Training with A Faster Gradient Variant )
The Python source codes are 'xperiment 11. AdagradWith.25XTXasG vs. Adagrad MNIST.py' and 'Experiment 11. NesterovWith.25XTXasG vs. Nesterov MNIST.py', in the '/data' folder.
On a Ubuntu cloud, our implementation requires the following libraries in order:
g++
:
# apt install g++
make
:
# apt install make
m4
: #
# apt install m4
GMP
(ver. 6.1.2):
# cd gmp-x.x.x
# ./configure --enable-cxx
# make
# make install
# ldconfig
NTL
(ver. 11.3.0):
# cd ntl-x.x.x
# cd src
# ./configure NTL_THREADS=on NTL_THREAD_BOOST=on NTL_EXCEPTIONS=on
# make
# make install
You need to configure and build the CNNinference project.
After that, in the 'Debug' folder, you can run our project by the following command lines:
# make clean
# make all
# ./MyIDASH2017
You can change the source codes and then repeat the above lines to debug your own project.
In the 'Debug' folder, you can find the C++ running results for six datasets:
'MyIDASH2017ArchiveFile20240128_SetNumThreads(36)_kdeg5_numIter4_fold10_Blogp40_idash18x1579.txt_nohup.out'
'MyIDASH2017ArchiveFile20240128_SetNumThreads(36)_kdeg5_numIter4_fold05_Blogp40_edin.txt_nohup.out'
'MyIDASH2017ArchiveFile20240128_SetNumThreads(36)_kdeg5_numIter4_fold05_Blogp40_lbw.txt_nohup.out'
'MyIDASH2017ArchiveFile20240128_SetNumThreads(36)_kdeg5_numIter4_fold05_Blogp40_nhanes3.txt_nohup.out'
'MyIDASH2017ArchiveFile20240128_SetNumThreads(36)_kdeg5_numIter4_fold05_Blogp40_pcs.txt_nohup.out'
'MyIDASH2017ArchiveFile20240128_SetNumThreads(36)_kdeg5_numIter4_fold05_Blogp40_uis.txt_nohup.out'