ADMM attack: an enhanced adversarial attack for deep neural networks with undetectable distortions. Authors: Pu Zhao. Pu Zhao. Northeastern University. View ...

Jan 24, 2019 · The experimental results demonstrate that the proposed ADMM attacks achieve both the high attack success rate and the mini- mal distortion for ...

Jan 21, 2019 · The experimental results demonstrate that the proposed ADMM attacks achieve both the high attack success rate and the minimal distortion for the ...

Adversarial examples in adversarial attacks: – adding delicately crafted distortions onto original legal inputs, can mislead a. DNN to classify them as any ...

This work proposes a general framework for constructing adversarial examples by leveraging Alternating Direction Method of Multipliers (ADMM) to split the ...

Deep neural networks (DNNs) are known vulnerable to adversarial attacks. That is, adversarial examples, obtained by adding delicately crafted distortions onto ...

ADMM attack: An enhanced adversarial attack for deep neural networks with undetectable distortions. Pu Zhao, Kaidi Xu, Sijia Liu, Yanzhi Wang, Xue Lin.

Deep neural networks (DNNs) are known vulnerable to adversarial attacks. That is, adversarial examples, obtained by adding delicately crafted distortions ...

Admm attack: an enhanced adversarial attack for deep neural networks with undetectable distortions. Many recent studies demonstrate that state-of-the-art ...

ADMM attack: An enhanced adversarial attack for deep neural networks with undetectable distortions. Pu Zhao; Kaidi Xu; et al. 2019; ASP-DAC 2019. An ADMM-based ...