Example model inversion attack

This section will create a Jupyter Notebook to demonstrate a model inversion attack on a pretrained convolutional neural network (CNN) for the CIFAR-10 dataset using Keras and the ART. This example will include an initialization with an average image, similar to the approach in other ART sample notebooks:

1. Import the libraries we will use and initialize a random seed for our experiment:

   # Import necessary libraries
   import numpy as np
   import matplotlib.pyplot as plt
   from keras.models import load_model
   from keras.datasets import cifar10
   from art.attacks.inversion import ModelInversionAttack
   from art.estimators.classification import KerasClassifier
   # Set random seed for reproducibility
   np.random.seed(123)

2. Using Keras, we load our CIFAR-10 model as usual and create an ART classifier to use:

   # Load the pretrained CIFAR-10 model
   model = load_model(models/cifar10_model.h5')
   # Wrap the model with ART's KerasClassifier
   classifier = KerasClassifier...