Adversarial Attacks and Defences Competition

Alexey Kurakin,Ian Goodfellow,Samy Bengio,Yinpeng Dong,Fangzhou Liao,Ming Liang,Tianyu Pang,Jun Zhu,Xiaolin Hu,Cihang Xie,Jianyu Wang,Zhishuai Zhang,Zhou Ren,Alan Yuille,Sangxia Huang,Yao Zhao, Yuzhe Zhao,Zhonglin Han,Junjiajia Long, Yerkebulan Berdibekov,Takuya Akiba,Seiya Tokui, Motoki Abe

Springer Series on Challenges in Machine Learning（2018）

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摘要

To accelerate research on adversarial examples and robustness of machine learning classifiers, Google Brain organized a NIPS 2017 competition that encouraged researchers to develop new methods to generate adversarial examples as well as to develop new ways to defend against them. In this chapter, we describe the structure and organization of the competition and the solutions developed by several of the top-placing teams.

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关键词

Adversarial Examples, Adversarial Training, Gradient Masking, Adversarial Images, Worst-case Scores

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