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Examples of white-box attacks include among others, methods such as the Fast Gradient Sign Method (FGSM) [10], or Projected Gradient Descent (PGD) [11]. The Fast Gradient Sign Method works by introducing a small amount of noise to the image, which is indistinguishable by the human eye. The direction of this noise is the same as the gradient of the

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Gist for projected gradient descent adversarial attack using PyTorch. Raw. projected_gradient_descent.py. import torch. def projected_gradient_descent ( model, x, y, loss_fn, num_steps, step_size, step_norm, eps, eps_norm, clamp= ( 0, 1 ), y_target=None ): """Performs the projected gradient descent attack on a batch of images.""".

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4 Gradient Descent for Multivariate Linear Regression. Gradient Descent. Suppose we have a cost function $J$ and want to minimize it. Machine Learning Bookcamp: Learn machine learning by doing projects.

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def projected_gradient_descent(model, x, y, loss_fn, num_steps, step_size, step_norm, eps, eps_norm, clamp=(0,1), y_target=None): """Performs the projected gradient descent attack on a batch of images."""

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• Now, we illustrate another attack, a variant of FGSM applied iteratively with projection. • The attack uses Projected Gradient Descent (PGD) and is referred to as a PGD attack. • This is a commonly used attack for adversarial training: training the network to be robust. Another attack…often used during training

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Solve using Projected Gradient Descent (Madryet al.’ 17, Goodfellowet al.’15, Carlini& Wagner ‘16) ... §Adversarial training for additive attacks (Madryet

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