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International Workshop on Information Hiding

IH 2009: Information Hiding pp 73–88Cite as

Estimating Steganographic Fisher Information in Real Images

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 5806))

Abstract

This paper is concerned with the estimation of steganographic capacity in digital images, using information theoretic bounds and very large-scale experiments to approximate the distributions of genuine covers. The complete distribution cannot be estimated, but with carefully-chosen algorithms and a large corpus we can make local approximations by considering groups of pixels. A simple estimator for the local quadratic term of Kullback-Leibler divergence (Steganographic Fisher Information) is presented, validated on some synthetic images, and computed for a corpus of covers. The results are interesting not so much for their concrete capacity estimates but for the comparisons they provide between different embedding operations, between the information found in differently-sized and -shaped pixel groups, and the results of DC normalization within pixel groups. This work suggests lessons for the future design of spatial-domain steganalysis, and also the optimization of embedding functions.

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Author information

Authors and Affiliations

  1. Oxford University Computing Laboratory, Parks Road, Oxford, OX1 3QD, England

    Andrew D. Ker

Authors
  1. Andrew D. Ker
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Editor information

Editors and Affiliations

  1. Security Engineering Group, Technische Universität Darmstadt, Hochschulstr. 10, 64289, Darmstadt, Germany

    Stefan Katzenbeisser

  2. Horst Görtz Institute for IT Security, Ruhr-Universität Bochum, Bochum, Germany

    Ahmad-Reza Sadeghi

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© 2009 Springer-Verlag Berlin Heidelberg

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Ker, A.D. (2009). Estimating Steganographic Fisher Information in Real Images. In: Katzenbeisser, S., Sadeghi, AR. (eds) Information Hiding. IH 2009. Lecture Notes in Computer Science, vol 5806. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04431-1_6

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  • DOI: https://doi.org/10.1007/978-3-642-04431-1_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04430-4

  • Online ISBN: 978-3-642-04431-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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