Trusted AI in Multiagent Systems: An Overview of Privacy and Security for Distributed Learning-Reference-Cited by-同舟云学术

Trusted AI in Multiagent Systems: An Overview of Privacy and Security for Distributed Learning

Author:

Ma Chuan¹^ORCID,Li Jun²^ORCID,Wei Kang¹^ORCID,Liu Bo³^ORCID,Ding Ming⁴^ORCID,Yuan Long⁵^ORCID,Han Zhu⁶^ORCID,Vincent Poor H.⁷^ORCID

Affiliation:

1. Zhejiang Laboratory, Hangzhou, China

2. School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, China

3. School of Computer Science, University of Technology Sydney, Sydney, NSW, Australia

4. Data61, CSIRO, Sydney, NSW, Australia

5. School of Computer Science, Nanjing University of Science and Technology, Nanjing, China

6. Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA

7. Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ, USA

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Science and Technology on Information Systems Engineering Laboratory

Future Network Grant of Provincial Education Board in Jiangsu

Youth Foundation Project of Zhejiang Laboratory

Research Initiation Project of Zhejiang Laboratory

U.S. National Science Foundation, U.S. Department of Transportation, Toyota and Amazon

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

Reference324 articles.

1. Explaining and harnessing adversarial examples;goodfellow;arXiv 1412 6572,2014

5. When does machine learning FAIL? Generalized transferability for evasion and poisoning attacks;suciu;Proc Usenix Secur Symp,2018

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