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We assess the variability of PRNU-based camera fingerprints with mismatchedimaging pipelines (e.g., different camera ISP or digital darkroom software). Weshow that camera fingerprints exhibit non-negligible variations in this setup,which may lead to unexpected degradation of detection statistics in real-worlduse-cases. We tested 13 different pipelines, including standard digitaldarkroom software and recent neural-networks. We observed that correlationbetween fingerprints from mismatched pipelines drops on average to 0.38 and thePCE detection statistic drops by over 40%. The degradation in error rates isthe strongest for small patches commonly used in photo manipulation detection,and when neural networks are used for photo development. At a fixed 0.5% FPRsetting, the TPR drops by 17 ppt (percentage points) for 128 px and 256 pxpatches.

Empirical Evaluation of PRNU Fingerprint Variation for Mismatched Imaging Pipelines