Deep Learning-Based RF Fingerprint Identification With Channel Effects Mitigation-Reference-Cited by-同舟云学术

Deep Learning-Based RF Fingerprint Identification With Channel Effects Mitigation

Published:2023 Issue: Volume:4 Page:1668-1681
ISSN:2644-125X
Container-title:IEEE Open Journal of the Communications Society
language:
Short-container-title:IEEE Open J. Commun. Soc.

Author:

Fu Hua¹^ORCID,Peng Linning¹^ORCID,Liu Ming²^ORCID,Hu Aiqun³^ORCID

Affiliation:

1. School of Cyber Science and Engineering, Southeast University, Nanjing, China

2. Engineering Research Center of Network Management Technology for High Speed Railway of Ministry of Education, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China

3. Frontier Crossing Scientific Research Center, Purple Mountain Laboratories for Network and Communication Security, Nanjing, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Guangdong Key Research and Development Program

Jiangsu Provincial Key Laboratory of Network and Information Security

Purple Mountain Laboratories

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications

Link

http://xplorestaging.ieee.org/ielx7/8782661/10008219/10184130.pdf?arnumber=10184130

Reference65 articles.

1. Radio Identity Verification-Based IoT Security Using RF-DNA Fingerprints and SVM

2. Specific Emitter Identification Based on Variational Mode Decomposition and Spectral Features in Single Hop and Relaying Scenarios

3. Orientation and Channel Independent RF Fingerprinting for 5G IEEE 802.11ad Devices

4. Variational Mode Decomposition-Based Radio Frequency Fingerprinting of Bluetooth Devices

5. Intrusion Detection for IoT Devices based on RF Fingerprinting using Deep Learning

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