Secrecy-Driven Energy Minimization in Federated-Learning-Assisted Marine Digital Twin Networks-Reference-Cited by-同舟云学术

Secrecy-Driven Energy Minimization in Federated-Learning-Assisted Marine Digital Twin Networks

Author:

Qian Li Ping¹^ORCID,Li Mingqing¹^ORCID,Ye Ping¹,Wang Qian¹^ORCID,Lin Bin²^ORCID,Wu Yuan²^ORCID,Yang Xiaoniu³^ORCID

Affiliation:

1. College of Information Engineering, Zhejiang University of Technology, Hangzhou, China

2. Department of Communication Engineering, Dalian Maritime University, Dalian, China

3. Institute of Cyberspace Security, Zhejiang University of Technology, Hangzhou, China

Funder

Intergovernmental International Cooperation in Science and Technology Innovation Program

National Natural Science Foundation of China

Liaoning Revitalization Talents Program

Major Key Project of PCL

FDCT-MOST

FDCT

Basic and Applied Basic Research Foundation of Guangdong Province

Research Grant of University of Macau

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

Reference52 articles.

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2. Digital Twin Applications in Unmanned Surface Vehicles: A Survey;2023 6th International Conference on Software Engineering and Computer Science (CSECS);2023-12-22