Biologically inspired protection of deep networks from adversarial attacks

27 Mar 2017 Aran Nayebi Surya Ganguli

Inspired by biophysical principles underlying nonlinear dendritic computation in neural circuits, we develop a scheme to train deep neural networks to make them robust to adversarial attacks. Our scheme generates highly nonlinear, saturated neural networks that achieve state of the art performance on gradient based adversarial examples on MNIST, despite never being exposed to adversarially chosen examples during training... (read more)

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