Can Adversarial Weight Perturbations Inject Neural Backdoors-Reference-Cited by-同舟云学术

Can Adversarial Weight Perturbations Inject Neural Backdoors

Published:2020-10-19 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 29th ACM International Conference on Information & Knowledge Management
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Author:

Garg Siddhant¹,Kumar Adarsh¹,Goel Vibhor²,Liang Yingyu²

Affiliation:

1. Amazon Alexa, Manhattan Beach, CA, USA

2. University of Wisconsin-Madison, Madison, WI, USA

Funder

Office of the Vice Chancellor for Research and Graduate Education, University of Wisconsin-Madison

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3340531.3412130

Reference20 articles.

1. Moustafa Alzantot Yash Sharma Ahmed Elgohary Bo-Jhang Ho Mani Srivastava and Kai-Wei Chang. 2018. Generating Natural Language Adversarial Examples. Moustafa Alzantot Yash Sharma Ahmed Elgohary Bo-Jhang Ho Mani Srivastava and Kai-Wei Chang. 2018. Generating Natural Language Adversarial Examples.

2. Xinyun Chen Chang Liu Bo Li Kimberly Lu and Dawn Song. 2017. Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning. Xinyun Chen Chang Liu Bo Li Kimberly Lu and Dawn Song. 2017. Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning.

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