多探测器差分模糊测试用于伽马谱仪的篡改检测
Inter-detector differential fuzz testing for tamper detection in gamma spectrometers
AI总结：
本研究提出多探测器差分模糊测试方法，通过对比不同探测器的基线信号检测篡改，提升核 safeguards 和条约验证中的应用前景。
摘要：
我们扩展了物理差分模糊测试作为一种反篡改方法用于辐射探测器[Vavrek等，科学与全球安全2025]，以跨多个探测器单元进行比较。该方法先前被介绍为一种用于核 safeguards 和条约验证场景中验证单个辐射探测器的篡改检测方法，其通过随机采样探测器配置参数生成一系列光谱，形成未篡改系统的基线签名。在后来的潜在篡改发生后，使用相同的随机参数序列生成另一系列光谱，可以与基线进行比较。比较序列中的异常表明探测器行为的变化，这可能是由于篡改所致。该原始方法的一个限制是，一旦探测器已“下放”并可能被篡改，原始基线固定，如果需要在新参数下进行测试，则无法建立新的可信基线。在本工作中，我们将反篡改模糊测试概念扩展到多个探测器单元，使得下放探测器可以与可信或“黄金副本”探测器进行比较，即使存在正常的探测器间制造差异。我们使用三个NaI探测器展示了这种探测器间差分模糊测试能够检测代表性攻击，即使测试和黄金副本探测器来自不同制造商且性能不同。在此，检测篡改需要将比较度量值与参数值进行可视化，而不仅仅是样本数量；此外，该基线是非线性的，可能需要比简单阈值更复杂的异常检测方法。总体而言，这种扩展到多个探测器的方法提高了在现实世界条约验证和保障情境中应用该技术的可能性。
英文摘要：
We extend physical differential fuzz testing as an anti-tamper method for radiation detectors [Vavrek et al., Science and Global Security 2025] to comparisons across multiple detector units. The method was previously introduced as a tamper detection method for authenticating a single radiation detector in nuclear safeguards and treaty verification scenarios, and works by randomly sampling detector configuration parameters to produce a sequence of spectra that form a baseline signature of an untampered system. At a later date, after potential tampering, the same random sequence of parameters is used to generate another series of spectra that can be compared against the baseline. Anomalies in the series of comparisons indicate changes in detector behavior, which may be due to tampering. One limitation of this original method is that once the detector has `gone downrange' and may have been tampered with, the original baseline is fixed, and a new trusted baseline can never be established if tests at new parameters are required. In this work, we extend our anti-tamper fuzz testing concept to multiple detector units, such that the downrange detector can be compared against a trusted or `golden copy' detector, even despite normal inter-detector manufacturing variations. We show using three NaI detectors that this inter-detector differential fuzz testing can detect a representative attack, even when the tested and golden copy detectors are from different manufacturers and have different performances. Here, detecting tampering requires visualizing the comparison metric vs. the parameter values and not just the sample number; moreover this baseline is non-linear and may require anomaly detection methods more complex than a simple threshold. Overall, this extension to multiple detectors improves prospects for operationalizing the technique in real-world treaty verification and safeguards contexts.
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