The Adobe Hidden Feature and its Impact ...
Document type :
Communication dans un congrès avec actes
Title :
The Adobe Hidden 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]
Conference title :
12th ACM Workshop on Information Hiding and Multimedia Security
City :
Baiona
Country :
Espagne
Start date of the conference :
2024-06-24
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 in [2,3,13] that images coming from several sensors were more prone to generate ...
Show more >If the extraction of sensor fingerprints represents nowadays an important forensic tool for sensor attribution, it has been shown recently in [2,3,13] 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 or Photoshop softwares. 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 per channel coded) to 8 bits-coded images also embed a periodic 128×128 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 in [13], we were able to prevent the False Positives. A discussion with Adobe representatives informed us that the company decided to add this pattern in order to induce dithering.Show less >
Show more >If the extraction of sensor fingerprints represents nowadays an important forensic tool for sensor attribution, it has been shown recently in [2,3,13] 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 or Photoshop softwares. 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 per channel coded) to 8 bits-coded images also embed a periodic 128×128 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 in [13], we were able to prevent the False Positives. A discussion with Adobe representatives informed us that the company decided to add this pattern in order to induce dithering.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
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