The Adobe Lightroom Secret Feature and its ...
Document type :
Pré-publication ou Document de travail: Autre communication scientifique (congrès sans actes - poster - séminaire...)
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Title :
The Adobe Lightroom Secret Feature and its Impact on Sensor Attribution
Author(s) :
Butora, Jan [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Bas, Patrick [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Bas, Patrick [Auteur]

Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
English keyword(s) :
PRNU
False-Positive
Watermarking
Watermark Removal
False-Positive
Watermarking
Watermark Removal
HAL domain(s) :
Sciences de l'ingénieur [physics]/Traitement du signal et de l'image [eess.SP]
English abstract : [en]
If the extraction of sensor fingerprints represents nowadays an important forensic tool for sensor attribution, it has been shown recently that images coming from several sensors were more prone to generate False Positives ...
Show more >If the extraction of sensor fingerprints represents nowadays an important forensic tool for sensor attribution, it has been shown recently that images coming from several sensors were more prone to generate False Positives (FP) by presenting a common "leak". In this paper, we investigate the possible cause of this leak and after inspecting the EXIF metadata of the sources causing FP, we found out that they were related to the Adobe Lightroom software. The cross-correlation between residuals on images presenting FP reveals periodic peaks showing the presence of a periodic pattern. By developing our own images with Adobe Lightroom we are able to show that all developments from raw images (or 16 bits-coded) to 8 bits-coded images also embed a periodic 128x128 pattern very similar to a watermark. However, we also show that the watermark depends on both the content and the architecture used to develop the image. The rest of the paper presents two different ways of removing this watermark, one by removing it from the image noise component, and the other by removing it in the pixel domain. We show that for a camera presenting FP, we were able to prevent the False Positives. A question remains on why Adobe decided to implement such a feature in their software.Show less >
Show more >If the extraction of sensor fingerprints represents nowadays an important forensic tool for sensor attribution, it has been shown recently that images coming from several sensors were more prone to generate False Positives (FP) by presenting a common "leak". In this paper, we investigate the possible cause of this leak and after inspecting the EXIF metadata of the sources causing FP, we found out that they were related to the Adobe Lightroom software. The cross-correlation between residuals on images presenting FP reveals periodic peaks showing the presence of a periodic pattern. By developing our own images with Adobe Lightroom we are able to show that all developments from raw images (or 16 bits-coded) to 8 bits-coded images also embed a periodic 128x128 pattern very similar to a watermark. However, we also show that the watermark depends on both the content and the architecture used to develop the image. The rest of the paper presents two different ways of removing this watermark, one by removing it from the image noise component, and the other by removing it in the pixel domain. We show that for a camera presenting FP, we were able to prevent the False Positives. A question remains on why Adobe decided to implement such a feature in their software.Show less >
Language :
Anglais
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Source :
Submission date :
2023-12-16T03:05:13Z
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