A Review of Adversarial Attack and Defense for Classification Methods-Reference-Cited by-同舟云学术

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A Review of Adversarial Attack and Defense for Classification Methods

Published:2022-01-04 Issue: Volume: Page:1-17
ISSN:0003-1305
Container-title:The American Statistician
language:en
Short-container-title:The American Statistician

Author:

Li Yao¹,Cheng Minhao²,Hsieh Cho-Jui²,Lee Thomas C. M.³^ORCID

Affiliation:

1. Department of Statistics & Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC;

2. Department of Computer Science, University of California at Los Angeles, Los Angeles, CA;

3. Department of Statistics, University of California at Davis, Davis, CA

Funder

National Science Foundation

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,General Mathematics,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/00031305.2021.2006781

Reference104 articles.

1. Alzantot, M., Sharma, Y., Chakraborty, S., and Srivastava, M. (2018), “Genattack: Practical Black-Box Attacks With Gradient-Free Optimization,” arXiv preprint arXiv:1805.11090.

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