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Trust Region Based Adversarial Attack on Neural Networks
[article]
2018
arXiv
pre-print
Deep Neural Networks are quite vulnerable to adversarial perturbations. Current state-of-the-art adversarial attack methods typically require very time consuming hyper-parameter tuning, or require many iterations to solve an optimization based adversarial attack. To address this problem, we present a new family of trust region based adversarial attacks, with the goal of computing adversarial perturbations efficiently. We propose several attacks based on variants of the trust region optimization
arXiv:1812.06371v1
fatcat:fewoe6odfzg6vgxeoiwtnedcie