MLSec

It's a repository to implement some experiments on Machine Learning Security

Code Description

1. Data_Poisoning Directory

• label_poisoning_attack_svm.py

It aims to implement a data poisoning attack on labels with SVM classifier.

2. Membership_Inference Directory

The code under this directory is implementation of 17 S&P paper "Membership Inference Attacks Against Machine Learning Models" by Shokri et al.

• data_synthesis.py

It aims to implement Algorithm 1: Data Synthesis in paper.

• shadow_models.py

It aims to implement Shadow model technique in paper.

• attack_models.py

It aims to implement Membership Inference Attack according to paper.

• Experiment_CIFAR10.py

It aims to implement CIFAR-10 experiment in paper.

• nn_model.py

It completes the neural network code using Pytorch.

• utils.py

It completes the utils code.

# Please notice: the norm_all_batch_data.npy under the directory Membership_Inference/cifar10/norm_all_batch_data.npy is too large to upload.

I uploaded it to the link: https://pan.baidu.com/s/1uZaZhVYUiRXi3resfuJoiA

Reference

1. Paper

• [17 S&P] Membership Inference Attacks Against Machine Learning Models

• [15 IJSN Attribute Infenrence Attack] Hacking Smart Machines with Smarter Ones How to Extract Meaningful Data from Machine Learning Classifiers

2. Code

Membership Inference Attack:

• Paper code: https://github.com/csong27/membership-inference

• BielStela's experiment implementation: https://github.com/BielStela/membership_inference