论文标题
对不匹配成像管道的PRNU指纹变化的经验评估
Empirical Evaluation of PRNU Fingerprint Variation for Mismatched Imaging Pipelines
论文作者
论文摘要
我们评估了具有不匹配成像管道（例如不同的相机ISP或数字暗室软件）的基于PRNU的相机指纹的可变性。我们表明，相机指纹在此设置中表现出不可忽略的变化，这可能导致现实世界中用例中检测统计的意外降解。我们测试了13种不同的管道，包括标准的数字暗室软件和最近的神经网络。我们观察到，来自不匹配管道的指纹之间的相关性平均下降至0.38，而PCE检测统计量下降量下降了40％以上。错误率的降解是照片操纵检测中常用的小斑块，以及使用神经网络用于照片开发时。在固定的0.5％FPR设置下，TPR在128个PX和256个PX贴片中下降了17个PPT（百分比）。
We assess the variability of PRNU-based camera fingerprints with mismatched imaging pipelines (e.g., different camera ISP or digital darkroom software). We show that camera fingerprints exhibit non-negligible variations in this setup, which may lead to unexpected degradation of detection statistics in real-world use-cases. We tested 13 different pipelines, including standard digital darkroom software and recent neural-networks. We observed that correlation between fingerprints from mismatched pipelines drops on average to 0.38 and the PCE detection statistic drops by over 40%. The degradation in error rates is the strongest for small patches commonly used in photo manipulation detection, and when neural networks are used for photo development. At a fixed 0.5% FPR setting, the TPR drops by 17 ppt (percentage points) for 128 px and 256 px patches.
