Detecting adversarial examples via prediction difference for deep neural networks-Reference-Cited by-同舟云学术

Detecting adversarial examples via prediction difference for deep neural networks

Published:2019-10 Issue: Volume:501 Page:182-192
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Guo Feng,Zhao Qingjie,Li Xuan,Kuang Xiaohui,Zhang Jianwei,Han Yahong^ORCID,Tan Yu-an^ORCID

Funder

National Natural Science Foundation of China

China Scholarship Council

German Research Foundation

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference33 articles.

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2. Globally normalized transition-based neural networks;Andor,2016

3. Thermometer encoding: one hot way to resist adversarial examples;Buckman,2018

4. Adversarial examples are not easily detected: bypassing ten detection methods;Carlini,2017

5. Towards evaluating the robustness of neural networks;Carlini,2017

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