Facing the Cover-Source Mismatch on JPHide using Training-Set Design
Résumé
This short paper investigates the influence of the image processing pipeline (IPP) on the cover-source mismatch (CSM) for the popular JPHide steganographic scheme. We propose to deal with CSM by combining a forensics and a steganalysis approach. A multi-classifier is first trained to identify the IPP, and secondly a specific training set is designed to train a targeted classifier for steganal-ysis purposes. We show that the forensic step is immune to the steganographic embedding. The proposed IPP-informed steganaly-sis outperforms classical strategies based on training on a mixture of sources and we show that it can provide results close to a detector specifically trained on the appropriate source.
Origine : Fichiers produits par l'(les) auteur(s)
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