Statistical Correlation as a Forensic ...
Type de document :
Communication dans un congrès avec actes
DOI :
Titre :
Statistical Correlation as a Forensic Feature to Mitigate the Cover-Source Mismatch
Auteur(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]
Titre de la manifestation scientifique :
12th ACM Workshop on Information Hiding and Multimedia Security (ACM IH&MMSEC'24)
Ville :
Baiona
Pays :
Espagne
Date de début de la manifestation scientifique :
2024-06-24
Titre de l’ouvrage :
Proceedings of the 12th ACM Workshop on Information Hiding and Multimedia Security
Date de publication :
2024
Mot(s)-clé(s) en anglais :
steganalysis
cover-source mismatch
image processing pipeline
fingerprint
Forensics
cover-source mismatch
image processing pipeline
fingerprint
Forensics
Discipline(s) HAL :
Informatique [cs]/Multimédia [cs.MM]
Résumé en anglais : [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 ...
Lire la suite >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.Lire moins >
Lire la suite >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.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
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