Securing Deep Learning as a Service Against Adaptive High Frequency Attacks With MMCAT-Reference-Cited by-同舟云学术

Securing Deep Learning as a Service Against Adaptive High Frequency Attacks With MMCAT

Author:

Song Bingbing¹^ORCID,Wang Ruxin²^ORCID,Gao Song³^ORCID,Dong Yunyun³^ORCID,Liu Ling⁴^ORCID,Zhou Wei²^ORCID

Affiliation:

1. School of Information Science & Engineering, Yunnan University, Kunming, Yunnan, China

2. National Pilot School of Software and Engineering Research Center of Cyberspace, Yunnan University, Kunming, Yunnan, China

3. National Pilot School of Software, Yunnan University, Kunming, Yunnan, China

4. College of Computing, Georgia Institute of Technology, Atlanta, GA, USA

Funder

Yunnan Province Education Department Foundation

National Natural Science Foundation of China

Research and Application of Object detection based on Artificial Intelligence

Yunnan Province expert workstations

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Information Systems and Management,Computer Networks and Communications,Computer Science Applications,Hardware and Architecture

Link

Reference41 articles.

1. Robust local features for improving the generalization of adversarial training;song;Proc 8th Int Conf Learn Representations,2020

3. Theoretically principled trade-off between robustness and accuracy;zhang;Proc 36th Int Conf Mach Learn,2019

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