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Detecting Hidden Messages Using Higher-Order Statistics and Support Vector Machines

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Information Hiding (IH 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2578))

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Abstract

Techniques for information hiding have become increasingly more sophisticated and widespread. With high-resolution digital images as carriers, detecting hidden messages has become considerably more difficult. This paper describes an approach to detecting hidden messages in images that uses a wavelet-like decomposition to build higher-order statistical models of natural images. Support vector machines are then used to discriminate between untouched and adulterated images.

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Author information

Authors and Affiliations

  1. Dartmouth College, 03755, Hanover, NH, USA

    Siwei Lyu & Hany Farid

Authors
  1. Siwei Lyu
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  2. Hany Farid
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Editor information

Editors and Affiliations

  1. Microsoft Research Ltd., 7 J. J. Thomson Avenue, CB3 0FB, Cambridge, UK

    Fabien A. P. Petitcolas

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© 2003 Springer-Verlag Berlin Heidelberg

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Lyu, S., Farid, H. (2003). Detecting Hidden Messages Using Higher-Order Statistics and Support Vector Machines. In: Petitcolas, F.A.P. (eds) Information Hiding. IH 2002. Lecture Notes in Computer Science, vol 2578. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36415-3_22

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  • DOI: https://doi.org/10.1007/3-540-36415-3_22

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00421-9

  • Online ISBN: 978-3-540-36415-3

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