yzhaiustc/PP-CNN

Privacy Preserving Convolutional Neural Network using Homomorphic Encryption for secure inference

PP-CNN

Privacy Preserving CNN Inference over Homomorphic Encryption

Directory structure

pp-cnn
├── plaintext_experiment      # Train model (Python)
│   ├── mnist
│   │     ├── *.py
│   │     └── saved_models  # Model structure(.json) and weights(.h5)
│   ├── cifar-10
│         ├── *.py
│         └── saved_models  # Model structure(.json) and weights(.h5)
│
│
├── pp_cnn                    # Secure inference (C++)
    ├── datasets
    │     ├── cifar-10
    │     └── mnist
    ├── include              # Header files for library
    ├── secrets              # Store SEAL parameter and key files
    └── src
         ├── main.cpp
         ├── setup.cpp
         ├── cnn
         └── utils

Requirement

• GCC (7.4.0)
• CMake (>=3.15)
• SEAL (3.4.4)
• Boost (Use boost::multi_array & boost::program_options)
• HDF5
  • Require zlib & szip

[Model training] (Python)

• Keras(2.0.8)
• tensorflow-gpu(1.4.0)

Dataset

• MNIST (http://yann.lecun.com/exdb/mnist/)
• CIFAR-10 (https://www.cs.toronto.edu/~kriz/cifar.html)

Download MNIST dataset in pp_cnn/datasets/mnist/

$ mkdir -p pp_cnn/datasets/mnist && cd pp_cnn/datasets/mnist
$ wget http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz
$ wget http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz
$ wget http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz
$ wget http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz
$ gunzip *.gz

Download CIFAR-10 dataset in pp_cnn/datasets/cifar-10/

$ mkdir -p pp_cnn/datasets/cifar-10 && cd pp_cnn/datasets/cifar-10
$ wget https://www.cs.toronto.edu/~kriz/cifar-10-binary.tar.gz
$ tar zxvf cifar-10-binary.tar.gz
$ mv cifar-10-batches-bin/* ./ && rmdir cifar-10-batches-bin/

Train model

Model training code (Python) is in plaintext_experiment/

ex) MNIST dataset

$ cd plaintext_experiment/mnist
$ python HCNN.py --da

Build pp_cnn

You can build by executing the following commands:

$ cd pp_cnn/src
$ mkdir build && cd build
$ cmake ..
$ make

Run

1. Setup SEAL setting (setup.cpp)

$ cd pp_cnn/bin
$ ./setup -P 15 -L 5

2. Secure inference of test data (main.cpp)

$ cd pp_cnn/bin
$ OMP_NUM_THREADS=xx ./main -D mnist -M HCNN-DA

License

Copyright 2020 Yamana Laboratory, Waseda University Supported by JST CREST Grant Number JPMJCR1503, Japan.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.