PRADA: Protecting Against DNN Model Stealing Attacks

This repo contains code that allows you to easily integrate the model stealing defense introduced in PRADA: Protecting Against DNN Model Stealing Attacks paper and presented at EuroS&P 2019. It consists of a) a self-contained defense agent b) a small wrapper that allows you to query the model (through the defense agent). Link to the arxiv version.

Requirements

• Python3
• pytorch
• torchvision
• numpy
• scipy
• matplotlib
• flask
• requests

Usage

• Interactive querying mode: python main.py.

• Provide path to the importable pytorch model.

• Simple post client included for the interactive mode: python client.py server_url image_file by default model is served at http://localhost:8080/predict.

Hence an example query: py client.py http://localhost:8080/predict cat.ppm

• Code contains additional comments for running the experiment with your model and data