Empirical Evaluation of PRNU Fingerprint Variation for Mismatched Imaging Pipelines

04/04/2020

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by   Sharad Joshi, et al.

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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 strongest for small patches commonly used in photo manipulation detection, and when neural networks are used for photo development. At a fixed 0.5 setting, the TPR drops by 17 ppt (percentage points) for 128 px and 256 px patches.