Improving Adversarial Robustness of Ensembles with Diversity Training

28 Jan 2019Sanjay KariyappaMoinuddin K. Qureshi

Deep Neural Networks are vulnerable to adversarial attacks even in settings where the attacker has no direct access to the model being attacked. Such attacks usually rely on the principle of transferability, whereby an attack crafted on a surrogate model tends to transfer to the target model... (read more)

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