This is the repo for our paper "Fake Gradient: A Security and Privacy Protection Framework for DNN-based Image Classification"
This folder contains the source code for our Fake Gradient:
Experiment Environment: This code is developed with Python 3.7 Pytorch 1.0 and OpenCV4.0 The DNN models used here are from the torchvision libraries.
The files are organized as below:
FakeGradient:
|
|
|---------ModelModify.py: contains the core functions that modify the model
|
|---------DeepFoolB.py: the original code of Deepfool
|
|---------DeepFoolC.py: the original code of Deepfool with minor modification for
| displaying the parameters of the modified model
|
|---------HeatMapShow.py: contains functions to process and visualize the
gradient/perturbation
|
|---------AnalysisWeight.py: Code to analyze the weights of fully connected layer
|
|---------MM21_classifiactionResult.py: The code to analyze the overhead
|
|
|---------MM21_FakeGradient_DeepFool_XXXX.py: The code to analyze defense
| accuracy based on Model XXXX