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Adaptive Steganography and Steganalysis with Fixed-Size Embedding

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Transactions on Data Hiding and Multimedia Security X

Part of the book series: Lecture Notes in Computer Science ((TDHMS,volume 8948))

Abstract

We analyze a two-player zero-sum game between a steganographer, Alice, and a steganalyst, Eve. In this game, Alice wants to hide a secret message of length \(k\) in a binary sequence, and Eve wants to detect whether a secret message is present. The individual positions of all binary sequences are independently distributed, but have different levels of predictability. Using knowledge of this distribution, Alice randomizes over all possible size-\(k\) subsets of embedding positions. Eve uses an optimal (possibly randomized) decision rule that considers all positions, and incorporates knowledge of both the sequence distribution and Alice’s embedding strategy.

Our model extends prior work by removing restrictions on Eve’s detection power. We give defining formulas for each player’s best response strategy and minimax strategy; and we present additional structural constraints on the game’s equilibria. For the special case of length-two binary sequences, we compute explicit equilibria and provide numerical illustrations.

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Notes

  1. 1.

    See [27] for an introduction to the area of information hiding.

  2. 2.

    The payoff matrix and the zero sum property might be different if false positives and false negatives result in different profits, respectively losses.

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Acknowledgments

We thank the reviewers for their comments on an earlier version of this paper. We gratefully acknowledge support by the Penn State Institute for Cyber-Science. The second author’s research visit at Penn State was supported under Visiting Scientists Grant N62909-13-1-V029 by the Office of Naval Research (ONR), and the third author’s research visit at Penn State was supported by the Campus Hungary Program.

Author information

Authors and Affiliations

  1. Cylab, Carnegie Mellon University, Pittsburgh, USA

    Benjamin Johnson

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

    Pascal Schöttle & Rainer Böhme

  3. Institute for Software Integrated Systems, Vanderbilt University, Nashville, USA

    Aron Laszka

  4. College of Information Sciences and Technology, Pennsylvania State University, University Park, USA

    Jens Grossklags

  5. School of Information, University of California, Berkeley, Berkeley, USA

    Benjamin Johnson

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  1. Benjamin Johnson
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Correspondence to Aron Laszka .

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Editors and Affiliations

  1. New Jersey Institute of Technology, Newark, New Jersey, USA

    Yun Q. Shi

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Johnson, B., Schöttle, P., Laszka, A., Grossklags, J., Böhme, R. (2015). Adaptive Steganography and Steganalysis with Fixed-Size Embedding. In: Shi, Y. (eds) Transactions on Data Hiding and Multimedia Security X. Lecture Notes in Computer Science(), vol 8948. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46739-8_5

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  • DOI: https://doi.org/10.1007/978-3-662-46739-8_5

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