Information-theoretic analysis of steganalysis in real images

ABSTRACT

In this paper we consider the problem of performance improvement of non-blind statistical steganalysis of additive steganography in real images. The proposed approach differs from the existing solutions in two main aspects:(a) a locally non-stationary Gaussian model is introduced via source splitting to represent the statistics of the cover image and (b)the detection of the hidden information is performed not from all but from those channels that allow to perform it with the required accuracy. We analyze the theoretically attainable bounds in such a framework and compare them to the corresponding limits of the existing state-of-the-art frameworks. The performed analysis demonstrates the superiority of the proposed approach.

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.4 INFORMATION SYSTEMS APPLICATIONS

General Terms:
Performance

Keywords:
parallel source splitting, steganalysi, steganograph