DeepFool -- A simple and accurate method to fool deep Neural Networks.

Let's go over the Algorithm: 1. The algorithm takes an input x and a classifier f . And the loop variable to 1. 4. Start and continue loop while the true label and the label of the adversarially perturbed image is the same. 5. Calculate the projection of the input onto the closest hyperplane. With multiclass classifiers, let's say the input is x and for each class there is a hyperplane (straight plane that divides one class from the others) and based on the place in the space where x lies it is classified into a class. Now, all this algorithm does is, it finds the closest hyperplane, and then projects x onto that hyperplane and pushes it a bit beyond, thus misclassifying it with the minimal perturbation possible.