notebooks/attack_parallel_auto_attack.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Evaluating Robustness by executing AutoAttack in parallel"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook demonstrates executing multiple attacks in parallel using AutoAttack. The __parallel__ mode of AutoAttack facilitates identifying attacks which are robust such that they successful fool an image classifier, and generate adversarial images which have fewer perturbations added, thus closer resembling the original image making it harder for it to be detected as malicious."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from art.attacks.evasion.auto_attack import AutoAttack\n",
    "from art.estimators.classification.pytorch import PyTorchClassifier\n",
    "import numpy as np\n",
    "import os\n",
    "from tests.utils import load_dataset\n",
    "import torch\n",
    "from art.attacks.evasion.projected_gradient_descent.projected_gradient_descent_pytorch import ProjectedGradientDescentPyTorch\n",
    "from art.attacks.evasion.deepfool import DeepFool\n",
    "from art.attacks.evasion.square_attack import SquareAttack\n",
    "from tests.utils import get_cifar10_image_classifier_pt\n",
    "import matplotlib.pyplot as plt\n",
    "from art.utils import load_dataset\n",
    "\n",
    "import logging\n",
    "logger = logging.getLogger()\n",
    "logger.setLevel(logging.WARNING)\n",
    "\n",
    "(x_train, y_train), (x_test, y_test), min_, max_ = load_dataset('cifar10')\n",
    "i = 10\n",
    "x_train = x_train[:i, :].transpose(0, 3, 1, 2).astype('float32')\n",
    "x_test = x_test[:i, :].transpose(0, 3, 1, 2).astype('float32')\n",
    "y_train = y_train[:i, :].astype('float32')\n",
    "y_test = y_test[:i, :].astype('float32')\n",
    "\n",
    "labels = ['airplane', 'automobile', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Example prediction using classifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "classifier = get_cifar10_image_classifier_pt()\n",
    "preds = classifier.predict(x_train)\n",
    "\n",
    "f, ax = plt.subplots(1, 1, constrained_layout = False)\n",
    "ax.set_title(f'Pred: {labels[np.argmax(y_train[0])]}\\nGround Truth: {labels[np.argmax(preds[[0]])]}')\n",
    "ax.imshow(x_train[0].transpose(1,2,0))\n",
    "ax.set_xlabel('Original Image')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Create a number of differently initialized attacks to test\n",
    "- vary the max_iter values, all others fixed\n",
    "- vary the eps_step values, all others fixed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "max_iter values: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20]\n",
      "eps_step values: [0.001, 0.011, 0.021, 0.031, 0.041, 0.051, 0.061, 0.071, 0.081, 0.091, 0.101, 0.111, 0.121, 0.131, 0.141, 0.151, 0.161, 0.171, 0.181, 0.191]\n",
      "Number of attacks: 40\n"
     ]
    }
   ],
   "source": [
    "n = 20\n",
    "attacks = []\n",
    "\n",
    "# create multiple values for max_iter\n",
    "max_iter = [i+1 for i in list(range(n))]\n",
    "print('max_iter values:', max_iter)\n",
    "\n",
    "# create multiple values for eps\n",
    "eps_steps = [round(float(i/100+0.001), 3) for i in list(range(n))]\n",
    "print('eps_step values:', eps_steps)\n",
    "\n",
    "for i, eps_step in enumerate(eps_steps):\n",
    "    attacks.append(\n",
    "        ProjectedGradientDescentPyTorch(\n",
    "            estimator=classifier,\n",
    "            norm=np.inf,\n",
    "            eps=0.1,\n",
    "            eps_step=eps_step,\n",
    "            max_iter=10,\n",
    "            targeted=False,\n",
    "            batch_size=32,\n",
    "            verbose=False\n",
    "        )\n",
    "    )\n",
    "    attacks.append(\n",
    "        ProjectedGradientDescentPyTorch(\n",
    "            estimator=classifier,\n",
    "            norm=np.inf,\n",
    "            eps=0.1,\n",
    "            max_iter=max_iter[i],\n",
    "            targeted=False,\n",
    "            batch_size=32,\n",
    "            verbose=False\n",
    "        )\n",
    "    )\n",
    "    \n",
    "print('Number of attacks:', len(attacks))\n",
    "attack_parallel = AutoAttack(estimator=classifier, attacks=attacks, targeted=True, parallel=True)\n",
    "attack_non_parallel = AutoAttack(estimator=classifier, attacks=attacks, targeted=True)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Run the attack\n",
    "- using non-parallel AutoAttack\n",
    "- using parallel AutoAttack"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/kieranfraser/git/personal/art/env/lib/python3.9/multiprocessing/resource_tracker.py:216: UserWarning: resource_tracker: There appear to be 1 leaked semaphore objects to clean up at shutdown\n",
      "  warnings.warn('resource_tracker: There appear to be %d '\n",
      "/Users/kieranfraser/git/personal/art/env/lib/python3.9/multiprocessing/resource_tracker.py:216: UserWarning: resource_tracker: There appear to be 1 leaked semaphore objects to clean up at shutdown\n",
      "  warnings.warn('resource_tracker: There appear to be %d '\n",
      "/Users/kieranfraser/git/personal/art/env/lib/python3.9/multiprocessing/resource_tracker.py:216: UserWarning: resource_tracker: There appear to be 1 leaked semaphore objects to clean up at shutdown\n",
      "  warnings.warn('resource_tracker: There appear to be %d '\n",
      "/Users/kieranfraser/git/personal/art/env/lib/python3.9/multiprocessing/resource_tracker.py:229: UserWarning: resource_tracker: '/loky-2595-nh_wgd4i': [Errno 2] No such file or directory\n",
      "  warnings.warn('resource_tracker: %r: %s' % (name, e))\n"
     ]
    }
   ],
   "source": [
    "# Run ART attack in non-parallel mode\n",
    "nonparallel_adv = attack_non_parallel.generate(x=x_train, y=y_train)\n",
    "\n",
    "# Run ART attack in parallel mode\n",
    "parallel_adv = attack_parallel.generate(x=x_train, y=y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Is the attack robust?\n",
    "If the attack is robust, predictions for each image will be incorrect and therefore the attack is fully robust."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Is AutoAttack non-parallel fully robust: True\n",
      "Is AutoAttack parallel fully robust: True\n"
     ]
    }
   ],
   "source": [
    "predictions_parallel = np.sum(np.argmax(classifier.predict(parallel_adv), axis=1) == np.argmax(y_train, axis=1)) == 0\n",
    "predictions_notparallel = np.sum(np.argmax(classifier.predict(nonparallel_adv), axis=1) == np.argmax(y_train, axis=1)) == 0\n",
    "\n",
    "print(f'Is AutoAttack non-parallel fully robust: {predictions_notparallel}')\n",
    "print(f'Is AutoAttack parallel fully robust: {predictions_parallel}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Visualize the adversarial images and perturbations\n",
    "- The first column images is the original image. The title shows the ground truth label and the classifier prediction on the original image. Note that as we are passing ground truth labels to the __generate__ method, attacks won't add perturbations to images that are already misclassified. Perturbations are added to images in which the classifier made correct predictions. \n",
    "\n",
    "- The second column images are adversarial images generated by AutoAttack in non-parallel mode - these should be identical to ART core (this is a sanity check to ensure changes have not changed core functionality).\n",
    "\n",
    "- The fourth column images are adversarial images generated by AutoAttack in parallel mode. Note how parallel model achieves lower L2 distance between the original and adversarial image - as all jobs are run in parallel mode, more attacks can be evaluated and successful attacks with lower perturbations added can be selected."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1500x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in range(len(x_train)):\n",
    "    f, ax = plt.subplots(1,3, constrained_layout = False)\n",
    "\n",
    "    nonparallel_perturbation = np.linalg.norm(x_train[[i]] - nonparallel_adv[[i]])\n",
    "    parallel_perturbation = np.linalg.norm(x_train[[i]] - parallel_adv[[i]])\n",
    "\n",
    "    ax[0].set_title(f'Ground Truth: {labels[np.argmax(y_train[i])]}\\nPrediction: {labels[np.argmax(classifier.predict(x_train[i]))]}')\n",
    "    ax[0].imshow(x_train[i].transpose(1,2,0))\n",
    "    ax[0].set_xlabel('Original')\n",
    "\n",
    "    ax[1].set_title(f'{labels[np.argmax(classifier.predict(nonparallel_adv[i]))]} ($\\\\ell ^{2}$={nonparallel_perturbation:.5f})')\n",
    "    ax[1].imshow(x_train[i].transpose(1,2,0))\n",
    "    ax[1].set_xlabel('Non-parallel')\n",
    "\n",
    "    ax[2].set_title(f'{labels[np.argmax(classifier.predict(parallel_adv[i]))]} ($\\\\ell ^{2}$={parallel_perturbation:.5f})')\n",
    "    ax[2].imshow(x_train[i].transpose(1,2,0))\n",
    "    ax[2].set_xlabel('Parallel')\n",
    "    f.set_figwidth(15)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example with MNIST"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tests.utils import get_image_classifier_pt\n",
    "from art.attacks.evasion.deepfool import DeepFool\n",
    "from art.attacks.evasion.auto_attack import AutoAttack, AutoProjectedGradientDescent\n",
    "\n",
    "# Load MNIST data\n",
    "(x_train_mnist, y_train_mnist), (x_test_mnist, y_test_mnist), _, _ = load_dataset('mnist')\n",
    "\n",
    "x_train_mnist = np.reshape(x_train_mnist, (x_train_mnist.shape[0],) + (1, 28, 28)).astype(np.float32)\n",
    "x_test_mnist = np.reshape(x_test_mnist, (x_test_mnist.shape[0],) + (1, 28, 28)).astype(np.float32)\n",
    "\n",
    "n_train = 10\n",
    "n_test = 10\n",
    "x_train_mnist = x_train_mnist[:n_train]\n",
    "y_train_mnist = y_train_mnist[:n_train]\n",
    "x_test_mnist = x_test_mnist[:n_test]\n",
    "y_test_mnist = y_test_mnist[:n_test]\n",
    "\n",
    "classifier = get_image_classifier_pt(from_logits=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Define attacks to run in parallel "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/kieranfraser/git/personal/art/env/lib/python3.9/multiprocessing/resource_tracker.py:216: UserWarning: resource_tracker: There appear to be 1 leaked semaphore objects to clean up at shutdown\n",
      "  warnings.warn('resource_tracker: There appear to be %d '\n"
     ]
    }
   ],
   "source": [
    "norm = np.inf\n",
    "eps = 0.3\n",
    "eps_step = 0.1\n",
    "batch_size = 32\n",
    "\n",
    "attacks = list()\n",
    "attacks.append(\n",
    "    AutoProjectedGradientDescent(\n",
    "        estimator=classifier,\n",
    "        norm=norm,\n",
    "        eps=eps,\n",
    "        eps_step=eps_step,\n",
    "        max_iter=100,\n",
    "        targeted=True,\n",
    "        nb_random_init=5,\n",
    "        batch_size=batch_size,\n",
    "        loss_type=\"cross_entropy\",\n",
    "        verbose=False,\n",
    "    )\n",
    ")\n",
    "attacks.append(\n",
    "    AutoProjectedGradientDescent(\n",
    "        estimator=classifier,\n",
    "        norm=norm,\n",
    "        eps=eps,\n",
    "        eps_step=eps_step,\n",
    "        max_iter=100,\n",
    "        targeted=False,\n",
    "        nb_random_init=5,\n",
    "        batch_size=batch_size,\n",
    "        loss_type=\"difference_logits_ratio\",\n",
    "        verbose=False,\n",
    "    )\n",
    ")\n",
    "attacks.append(DeepFool(classifier=classifier, max_iter=100, epsilon=1e-6, nb_grads=3, batch_size=batch_size, verbose=False,))\n",
    "sa = SquareAttack(estimator=classifier, norm=norm, max_iter=5000, eps=eps, p_init=0.8, nb_restarts=5, verbose=False,)\n",
    "\n",
    "attacks.append(sa)\n",
    "\n",
    "attack = AutoAttack(\n",
    "    estimator=classifier,\n",
    "    norm=norm,\n",
    "    eps=eps,\n",
    "    eps_step=eps_step,\n",
    "    attacks=attacks,\n",
    "    batch_size=batch_size,\n",
    "    estimator_orig=None,\n",
    "    targeted=True,\n",
    "    parallel=True,\n",
    ")\n",
    "\n",
    "x_train_mnist_adv = attack.generate(x=x_train_mnist, y=y_train_mnist)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Visualize the performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = [0,1,2,3,4,5,6,7,8,9]\n",
    "\n",
    "for i in range(len(x_train_mnist)):\n",
    "    f, ax = plt.subplots(1,2)\n",
    "\n",
    "    perturbation = np.linalg.norm(x_train_mnist[[i]] - x_train_mnist_adv[[i]])\n",
    "\n",
    "    ax[0].set_title(f'Prediction: {labels[np.argmax(classifier.predict(x_train_mnist[i]))]}\\nGround Truth: {labels[np.argmax(y_train_mnist[[i]])]} ')\n",
    "    ax[0].imshow(x_train_mnist[i].transpose(1,2,0))\n",
    "    ax[0].set_xlabel('Original')\n",
    "\n",
    "    ax[1].set_title(f'{labels[np.argmax(classifier.predict(x_train_mnist_adv[i]))]} ($\\\\ell ^{2}$={perturbation:.5f})')\n",
    "    ax[1].imshow(x_train_mnist_adv[i].transpose(1,2,0))\n",
    "    ax[1].set_xlabel('Parallel attack')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}