Federated Learning in Intelligent Transportation Systems: Recent Applications and Open Problems-Reference-Cited by-同舟云学术

Federated Learning in Intelligent Transportation Systems: Recent Applications and Open Problems

Author:

Zhang Shiying¹,Li Jun¹^ORCID,Shi Long¹^ORCID,Ding Ming²^ORCID,Nguyen Dinh C.³^ORCID,Tan Wuzheng⁴^ORCID,Weng Jian⁴^ORCID,Han Zhu⁵^ORCID

Affiliation:

1. School of Electrical and Optical Engineering, Nanjing University of Science and Technology, Nanjing, China

2. Data61, CSIRO, Eveleigh, NSW, Australia

3. Department of Electrical and Computer Engineering, The University of Alabama in Huntsville, Huntsville, AL, USA

4. College of Cyber Security, Jinan University, Guangzhou, China

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

Funder

National Natural Science Foundation of China

Science and Technology Major Project of Tibetan Autonomous Region of China

National Joint Engineering Research Center of Network Security Detection and Protection Technology

Guangdong Key Laboratory of Data Security and Privacy Preserving

Research Center of Trustworthy AI

Jiangsu Specially-Appointed Professor Program 2021

NSF

US Department of Transportation, Toyota and Amazon

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

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3. Research on federal learning privacy protection based on secure multi-party computing;Proceedings of the 2024 3rd International Conference on Cyber Security, Artificial Intelligence and Digital Economy;2024-03