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If the extraction of sensor fingerprints represents nowadays an importantforensic tool for sensor attribution, it has been shown recently that imagescoming from several sensors were more prone to generate False Positives (FP) bypresenting a common "leak". In this paper, we investigate the possible cause ofthis leak and after inspecting the EXIF metadata of the sources causing FP, wefound out that they were related to the Adobe Lightroom or Photoshop softwares.The cross-correlation between residuals on images presenting FP revealsperiodic peaks showing the presence of a periodic pattern. By developing ourown images with Adobe Lightroom we are able to show that all developments fromraw images (or 16 bits per channel coded) to 8 bits-coded images also embed aperiodic 128x128 pattern very similar to a watermark. However, we also showthat the watermark depends on both the content and the architecture used todevelop the image. The rest of the paper presents two different ways ofremoving this watermark, one by removing it from the image noise component, andthe other by removing it in the pixel domain. We show that for a camerapresenting FP, we were able to prevent the False Positives. A discussion withAdobe representatives informed us that the company decided to add this patternin order to induce dithering.

The Adobe Hidden Feature and its Impact on Sensor Attribution