Statistical Correlation as a Forensic ...
Document type :
Communication dans un congrès avec actes
DOI :
Title :
Statistical Correlation as a Forensic Feature to Mitigate the Cover-Source Mismatch
Author(s) :
Mallet, Antoine [Auteur]
Université de Technologie de Troyes [UTT]
Bas, Patrick [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Cogranne, Rémi [Auteur]
Université de Technologie de Troyes [UTT]
Université de Technologie de Troyes [UTT]
Bas, Patrick [Auteur]
![refId](/themes/Mirage2//images/idref.png)
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Cogranne, Rémi [Auteur]
Université de Technologie de Troyes [UTT]
Conference title :
12th ACM Workshop on Information Hiding and Multimedia Security (ACM IH&MMSEC'24)
City :
Baiona
Country :
Espagne
Start date of the conference :
2024-06-24
Book title :
Proceedings of the 12th ACM Workshop on Information Hiding and Multimedia Security
Publication date :
2024
English keyword(s) :
steganalysis
cover-source mismatch
image processing pipeline
fingerprint
Forensics
cover-source mismatch
image processing pipeline
fingerprint
Forensics
HAL domain(s) :
Informatique [cs]/Multimédia [cs.MM]
English abstract : [en]
The present paper deals with the cover-source mismatch (CSM) problem in operational steganalysis. It first investigates the distribution of the noise in natural images, and shows how this property can be used to build a ...
Show more >The present paper deals with the cover-source mismatch (CSM) problem in operational steganalysis. It first investigates the distribution of the noise in natural images, and shows how this property can be used to build a fingerprint of the cover-source, to address the issue of source identification from a single image. In particular, fingerprints from different noise extraction techniques are studied. Results show that these fingerprints can be complementary. The method proposed in the present paper aggregates them in a unique forensic feature to build a more accurate source identification algorithm than when using steganalysis features, such as the discrete cosine transform residual (DCTR). Last, the paper exploits the proposed forensic tool to mitigate CSM via "atomistic steganalysis". Used together with steganalysis methods, experimental results highlight the superiority of our approach, as compared to other atomistic mitigation strategies. The relevancy of these results is further studied on out-of-camera images coming from Flickr and the ALASKA dataset. We show that for some devices, our approach gives results superior to the omniscient scenario.Show less >
Show more >The present paper deals with the cover-source mismatch (CSM) problem in operational steganalysis. It first investigates the distribution of the noise in natural images, and shows how this property can be used to build a fingerprint of the cover-source, to address the issue of source identification from a single image. In particular, fingerprints from different noise extraction techniques are studied. Results show that these fingerprints can be complementary. The method proposed in the present paper aggregates them in a unique forensic feature to build a more accurate source identification algorithm than when using steganalysis features, such as the discrete cosine transform residual (DCTR). Last, the paper exploits the proposed forensic tool to mitigate CSM via "atomistic steganalysis". Used together with steganalysis methods, experimental results highlight the superiority of our approach, as compared to other atomistic mitigation strategies. The relevancy of these results is further studied on out-of-camera images coming from Flickr and the ALASKA dataset. We show that for some devices, our approach gives results superior to the omniscient scenario.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
Source :
Files
- document
- Open access
- Access the document
- main_copy.pdf
- Open access
- Access the document