Abstract
According to Cachin’s steganography security criterion, if the statistical distributions of cover and stego images are identical, the hidden message is assumed undetectable. However, any steganographic method will surely cause some statistical distortions, which gives steganalyst a hint. This paper presents a steganalysis method for JPEG images based on Cachin criterion. It estimates the cover image from the stego one by using a small-scale geometrical transform, and then detects the statistical distortions between the cover and stego images based on some features, which are sensitive to the steganographic modifications. Then a classifier is trained on these features. Three different modern steganographic schemes are tested. Experimental results show that the proposed steganalysis scheme has better performance compared to the current steganalysis methods.
This work was supported by China 863 high tech plan (2003AA144080) and NSFC (60075002).
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Quan, X., Zhang, H., Dou, H. (2007). Steganalysis for JPEG Images Based on Statistical Features of Stego and Cover Images. In: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues. ICIC 2007. Lecture Notes in Computer Science, vol 4681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74171-8_98
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DOI: https://doi.org/10.1007/978-3-540-74171-8_98
Publisher Name: Springer, Berlin, Heidelberg
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