CW/DDN are adversarial attack methods that aim to compute the minimal epsilon for which an adversarial attack exist. However, their computational time is quite high. Both methods work by local search of the minimal epsilon.
In this project we therefore wish to examine an approximate of the minimal epsilon in order to reduce the computational complexity. We can estimate the epsilon according to the model accuracy on randomly corrupted data.