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| Hauptverfasser: | , , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2501.15391 |
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| _version_ | 1866910801299767296 |
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| author | Cai, Donghong Shan, Jiahao Gao, Ning He, Bingtao Chen, Yingyang Jin, Shi Fan, Pingzhi |
| author_facet | Cai, Donghong Shan, Jiahao Gao, Ning He, Bingtao Chen, Yingyang Jin, Shi Fan, Pingzhi |
| contents | Radio Frequency Fingerprinting Identification (RFFI) is a lightweight physical layer identity authentication technique. It identifies the radio-frequency device by analyzing the signal feature differences caused by the inevitable minor hardware impairments. However, existing RFFI methods based on closed-set recognition struggle to detect unknown unauthorized devices in open environments. Moreover, the feature interference among legitimate devices can further compromise identification accuracy. In this paper, we propose a joint radio frequency fingerprint prediction and siamese comparison (JRFFP-SC) framework for open set recognition. Specifically, we first employ a radio frequency fingerprint prediction network to predict the most probable category result. Then a detailed comparison among the test sample's features with registered samples is performed in a siamese network. The proposed JRFFP-SC framework eliminates inter-class interference and effectively addresses the challenges associated with open set identification. The simulation results show that our proposed JRFFP-SC framework can achieve excellent rogue device detection and generalization capability for classifying devices. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_15391 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Open Set RF Fingerprinting Identification: A Joint Prediction and Siamese Comparison Framework Cai, Donghong Shan, Jiahao Gao, Ning He, Bingtao Chen, Yingyang Jin, Shi Fan, Pingzhi Cryptography and Security Radio Frequency Fingerprinting Identification (RFFI) is a lightweight physical layer identity authentication technique. It identifies the radio-frequency device by analyzing the signal feature differences caused by the inevitable minor hardware impairments. However, existing RFFI methods based on closed-set recognition struggle to detect unknown unauthorized devices in open environments. Moreover, the feature interference among legitimate devices can further compromise identification accuracy. In this paper, we propose a joint radio frequency fingerprint prediction and siamese comparison (JRFFP-SC) framework for open set recognition. Specifically, we first employ a radio frequency fingerprint prediction network to predict the most probable category result. Then a detailed comparison among the test sample's features with registered samples is performed in a siamese network. The proposed JRFFP-SC framework eliminates inter-class interference and effectively addresses the challenges associated with open set identification. The simulation results show that our proposed JRFFP-SC framework can achieve excellent rogue device detection and generalization capability for classifying devices. |
| title | Open Set RF Fingerprinting Identification: A Joint Prediction and Siamese Comparison Framework |
| topic | Cryptography and Security |
| url | https://arxiv.org/abs/2501.15391 |