Radio Frequency Fingerprinting via Deep Learning: Challenges and Opportunities
Author:
Affiliation:
1. Hamad Bin Khalifa University (HBKU),College of Science and Engineering (CSE),Doha,Qatar
2. KTH Royal Institute of Technology,Networked Systems Security group,Stockholm,Sweden
3. Eindhoven University of Technology,Eindhoven,Netherlands
Funder
Qatar Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10592105/10592309/10592579.pdf?arnumber=10592579
Reference15 articles.
1. A Review of Radio Frequency Fingerprinting Techniques
2. PAST-AI: Physical-Layer Authentication of Satellite Transmitters via Deep Learning
3. Deep learning
4. A comprehensive survey on radio frequency (RF) fingerprinting: Traditional approaches, deep learning, and open challenges
5. WiSig: A Large-Scale WiFi Signal Dataset for Receiver and Channel Agnostic RF Fingerprinting
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