Physical Layer Authentication based on Integrated Semi-Supervised Learning in Wireless Networks for Dynamic Industrial Scenarios
Author:
Affiliation:
1. School of Cyberspace Security and Computer, Hebei University, Hebei, China
2. School of Systems Information Science, Future University Hakodate, Hakodate, Japan
Funder
National Natural Science Foundation of China
Key Research and Development Program of Hebei Province of China
Natural Science Foundation of Hebei Province of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Aerospace Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/25/4356907/09998124.pdf?arnumber=9998124
Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Adaptive Security in Mobile Wireless Networks: Machine Learning-Enhanced Continuous Physical Layer Authentication for Dynamic Environments;2024 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0 & IoT);2024-05-29
2. Physical Layer Authentication and Security Design in the Machine Learning Era;IEEE Communications Surveys & Tutorials;2024
3. Inter-Frame-Relationship Protected Signal: A New Design for Radio Frequency Fingerprint Authentication;Sensors;2023-08-04
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