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A Game-Theoretic Approach to Content-Adaptive Steganography

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Information Hiding (IH 2012)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 7692))

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Abstract

Content-adaptive embedding is widely believed to improve steganographic security over uniform random embedding. However, such security claims are often based on empirical results using steganalysis methods not designed to detect adaptive embedding. We propose a framework for content-adaptive embedding in the case of imperfect steganography. It formally defines heterogeneity within the cover as a necessary condition for adaptive embedding. We devise a game-theoretic model for the whole process including cover generation, adaptive embedding, and a detector which anticipates the adaptivity. Our solution exhibits a unique equilibrium in mixed strategies. Its location depends on the level of heterogeneity of the cover source, but never coincides with naïve adaptive embedding. The model makes several simplifying assumptions, including independent cover symbols and the steganalyst’s ability to recover the adaptivity criterion perfectly.

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Author information

Authors and Affiliations

  1. Department of Information Systems, University of Münster, Germany

    Pascal Schöttle & Rainer Böhme

Authors
  1. Pascal Schöttle
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  2. Rainer Böhme
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Editor information

Editors and Affiliations

  1. International Computer Science Institute, 1947 Center Street, Suite 600, 94704, Berkeley, CA, USA

    Matthias Kirchner

  2. Department of Computer Science, University of California Davis, 95616, Davis, CA, USA

    Dipak Ghosal

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Schöttle, P., Böhme, R. (2013). A Game-Theoretic Approach to Content-Adaptive Steganography. In: Kirchner, M., Ghosal, D. (eds) Information Hiding. IH 2012. Lecture Notes in Computer Science, vol 7692. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36373-3_9

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  • DOI: https://doi.org/10.1007/978-3-642-36373-3_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36372-6

  • Online ISBN: 978-3-642-36373-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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