Work

Selection-channel-aware rich model for Steganalysis of digital images

Year: 2014

Type: conference-paper

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 slection 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 popular spatial rich model (SRM) that makes use of the selection 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.

Source: IEEE International Workshop on Information Forensics and Security

DOI: 10.1109/wifs.2014.7084302

Authors: Tomas Denemark, Vahid Sedighi, Vojtech Holub, Remi Cogranne, Jessica Fridrich

Institution: Binghamton University

Language: English

Topic: Advanced Steganography and Watermarking Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2538511122

FWCI: 14.13

Cites: 19

Cited by: 397

Related to: 10