Apply Membership Inference Attack and Differential Privacy on Binary ML Classifier

Small dataset: Start with 10K and then scale it up.
Step 1. Train a normal deep learning classifier with a duplication based dataset
Step 2. Trying to run Membership Inference Attack (MIA) on this classifier

Step 3. Add Differential Privacy (DP) to train a new model with or without duplicate datasets.
Apply step 2 on it.

Use a binary classifier for the simple cases.

In Total train four classifiers.
Classifiers to train:
1. Classifier trained on data WITHOUT non-reoccurring information within samples and WITHOUT DP (+MIA)
2. Classifier trained on data WITH non-reoccurring information within samples and WITHOUT DP (+MIA)
3. Classifier trained on data WITHOUT non-reoccurring information within samples and WITH DP (+MIA)
4. Classifier trained on data WITH non-reoccurring information within samples and WITH DP (+MIA)

Further questions will be answered on request.