Authors
Tomáš Denemark, Vahid Sedighi, Vojtěch Holub, Rémi Cogranne, Jessica Fridrich,
Title
Selection-Channel-Aware Rich Model for Steganalysis of Digital Images
In
Proc. of IEEE International Workshop on Information Forensics and Security
Pages
1–5
Publisher
IEEE
Year
2014
Indexed by
Abstract
From the perspective of signal detection theory, it seems obvious that knowing the probabilities with which the individual cover elements are modified during message embedding (the so-called probabilistic selection channel) should improve steganalysis. It is, however, not clear how to incorporate this information into steganalysis features when the detector is built as a classifier. In this paper, we propose a variant of the pop- ular spatial rich model (SRM) that makes use of the se- lection channel. We demonstrate on three state-of-the- art content-adaptive steganographic schemes that even an imprecise knowledge of the embedding probabilities can substantially increase the detection accuracy in comparison with feature sets that do not consider the selection channel. Overly adaptive embedding schemes seem to be more vulnerable than schemes that spread the embedding changes more evenly throughout the cover.
Affiliations
Offprint