CRFeb 23, 2022

High-precision Hardware Oscillators Ensemble for GNSS Attack Detection

arXiv:2202.11483v21 citations
Originality Incremental advance
AI Analysis

This addresses security risks for GNSS-dependent applications by enabling attack detection during network disconnections, though it is incremental as it builds on existing clock-based methods.

The paper tackles the problem of detecting GNSS attacks by using an on-board ensemble of reference clocks, achieving detection of time offset modifications as low as 0.3 microseconds with half the latency compared to prior work.

A wide gamut of important applications rely on global navigation satellite systems (GNSS) for precise time and positioning. Attackers dictating the GNSS receiver position and time solution are a significant risk, especially due to the inherent vulnerability of GNSS systems. A first line of defense, for a large number of receivers, is to rely on additional information obtained through the rich connectivity of GNSS enabled platforms. Network time can be used for direct validation of the GNSS receiver time; but this depends on network availability. To allow attack detection even when there are prolonged network disconnections, we present a method based on on-board ensemble of reference clocks. This allows the receiver to detect sophisticated attacks affecting the GNSS time solution, independently of the specific attack methodology. Results obtained with Chip-Scale Oven Compensated Oscillators (CS-OCXO) are promising and demonstrate the potential of embedded ensembles of reference clocks, detecting attacks causing modifications of the receiver time offset as low as 0.3us, with half the detection latency compared to related literature.

Foundations

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