Attention is Needed for RF Fingerprinting

Author:

Gu Hanqing1,Su Lisheng1,Zhang Weifeng2ORCID,Ran Chuan3

Affiliation:

1. Zhejiang JEC Electronic Company Ltd, Zhejiang, China

2. College of Information Science and Engineering, Jiaxing University, Jiaxing, China

3. IBM Corporation, Durham, NC, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Reference45 articles.

1. Secure Industrial IoT Systems via RF Fingerprinting Under Impaired Channels With Interference and Noise

2. Embedding-Assisted Attentional Deep Learning for Real-World RF Fingerprinting of Bluetooth

3. A comprehensive survey on radio frequency (RF) fingerprinting: Traditional approaches, deep learning, and open challenges;jagannath;Comput Netw,2023

4. BEVT: BERT Pretraining of Video Transformers

5. Semi-supervised RF fingerprinting with consistency-based regularization;wang;arXiv 2304 14795,2023

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1. FeRHA: Fuzzy-Extractor-Based RF and Hardware Fingerprinting Two-Factor Authentication;Applied Sciences;2024-04-16

2. Research on LED fingerprint identification method based on convolutional neural network;Advanced Fiber Laser Conference (AFL2023);2024-03-18

3. Deep Learning Based RF Fingerprint Identification using Cyclic Shift Characteristic;2024 4th International Conference on Consumer Electronics and Computer Engineering (ICCECE);2024-01-12

4. Understanding Radio Frequency Fingerprint Identification With RiFyFi Virtual Databases;IEEE Open Journal of the Communications Society;2024

5. Efficient Channel-Temporal Attention for Boosting RF Fingerprinting;IEEE Open Journal of Signal Processing;2024

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