FAST: Adopting Federated Unlearning to Eliminating Malicious Terminals at Server Side-Reference-Cited by-同舟云学术

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FAST: Adopting Federated Unlearning to Eliminating Malicious Terminals at Server Side

Published:2023 Issue: Volume: Page:1-14
ISSN:2327-4697
Container-title:IEEE Transactions on Network Science and Engineering
language:
Short-container-title:IEEE Trans. Netw. Sci. Eng.

Author:

Guo Xintong¹,Wang Pengfei²,Qiu Sen³,Song Wei²,Zhang Qiang²,Wei Xiaopeng²,Zhou Dongsheng¹

Affiliation:

1. Key Laboratory of Advanced Design and Intelligent Computing (Ministry of Education), School of Software Engineering, Dalian University, Dalian, China

2. School of Computer Science and Technology, Dalian University of Technology, Dalian, China

3. School of Control Science and Engineering, Dalian University of Technology, Dalian, China

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

111 project

Support Plan for Key Field Innovation Team of Dalian

Open Project of Key Laboratory for Advanced Design and Intelligent Computing of the Ministry of Education

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/6488902/6930788/10360312.pdf?arnumber=10360312

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1. Anomaly detection and defense techniques in federated learning: a comprehensive review;Artificial Intelligence Review;2024-05-23

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