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.
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Böhme, R. (2005). Assessment of Steganalytic Methods Using Multiple Regression Models. In: Barni, M., Herrera-Joancomartí, J., Katzenbeisser, S., Pérez-González, F. (eds) Information Hiding. IH 2005. Lecture Notes in Computer Science, vol 3727. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11558859_21
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DOI: https://doi.org/10.1007/11558859_21
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