Titre :

Linking Intrinsic Difficulty and Regret to Properties of Multivariate Gaussians in Image Steganalysis

Auteur(s) :

Mallet, Antoine [Auteur]
Université de Technologie de Troyes [UTT]
Cogranne, Rémi [Auteur]
Université de Technologie de Troyes [UTT]
Bas, Patrick [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]

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 2024 ACM Workshop on Information Hiding and Multimedia Security (IHMMSec ’24)

Éditeur :

ACM

Date de publication :

2024

Mot(s)-clé(s) en anglais :

steganalysis
cover-source mismatch
image processing pipeline
fingerprint
Forensics

Discipline(s) HAL :

Informatique [cs]/Multimédia [cs.MM]

Résumé en anglais : [en]

This paper deals with the Cover-Source Mismatch (CSM) problem faced in operational steganalysis. Based on a multivariate Gaussian model of the distribution of the noise contained in natural images, it provides proxies for ...
Lire la suite >This paper deals with the Cover-Source Mismatch (CSM) problem faced in operational steganalysis. Based on a multivariate Gaussian model of the distribution of the noise contained in natural images, it provides proxies for the two important empirical measures of CSM: intrinsic difficulty and regret. The former can be modeled with the determinant of the covariance matrix of the noise present in an image. The latter can be predicted with a modified Kullback-Leibler divergence between the distribution of the noises of images coming from different cover-sources. We first recall the reasoning behind the multivariate Gaussian model of the noise, and detail how to compute the statistic of the distribution of the noise. Then, our proposed models are compared to empirical data with a specifically designed cover-source generation process. For both quantities, very high correlation coefficients between the model and the observations are obtained. Finally, realistic cover-sources are used to further illustrate the relevance of our model.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Projet ANR :

Protection contre les usages criminels de la stéganographie

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL