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Assessment of Steganalytic Methods Using Multiple Regression Models

  • Rainer Böhme
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3727)

Abstract

This paper proposes multiple regression models as a method for quantitative evaluation of the accuracy in steganalysis with respect to various moderating factors, such as parameter choice of the detector and properties of the carrier object. The case for multivariate statistical inference in steganalysis is particularly relevant: recent findings suggest that type and characteristics of carrier do matter, but the precise relations remain still opaque. In this paper we provide an exemplary comparison between two length-estimating attacks against LSB steganography. Extensions and applications for improved steganalysis are addressed.

Keywords

Multiple Regression Model Secret Message Information Hiding Stego Image Cauchy Distribution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Rainer Böhme
    • 1
  1. 1.Institute for System ArchitectureTechnische Universität DresdenDresdenGermany

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