AI Article Synopsis
- GNSS spoofing poses a significant security risk for remote sensing systems, prompting the need for improved identification methods of GNSS receivers.
- The paper introduces a new fingerprinting scheme that utilizes unique hardware noise from Chip-Scale Atomic Clocks (CSACs) in GNSS receivers to distinguish between devices of the same specification.
- Experiments demonstrated that this method achieved a 94.60% identification accuracy and effectively detected anomalies, offering a robust and real-time security monitoring solution compatible with commercial GNSS receivers.
Article Abstract
GNSS spoofing has become a significant security vulnerability threatening remote sensing systems. Hardware fingerprint-based GNSS receiver identification is one of the solutions to address this security issue. However, existing research has not provided a solution for distinguishing GNSS receivers of the same specification. This paper first theoretically proves that the CSACs (Chip-Scale Atomic Clocks) used in GNSS receivers have unique hardware noise and then proposes a fingerprinting scheme based on this hardware noise. Experiments based on the neural network method demonstrate that this fingerprint achieved an identification accuracy of 94.60% for commercial GNSS receivers of the same specification and performed excellently in anomaly detection, confirming the robustness of the fingerprinting method. This method shows a new real-time GNSS security monitoring method based on CSACs and can be easily used with any commercial GNSS receivers.
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Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11314955 | PMC |
| http://dx.doi.org/10.3390/s24154897 | DOI Listing |
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