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Steganalysis Based on Statistical Properties of the Encrypted Messages

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Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 10446))

Abstract

It is introduced a new steganalytic method based on investigation of statistical properties of the extracted encrypted messages. It is assumed that the message is encrypted before embedding by some sufficiently strong cipher. The extracted messages are exposed to the testing on pseudorandomness, namely to NIST-tests. When passing these tests, the tested objects are assumed stego-objects, otherwise as cover objects. Support vector machine methodology is used to improve the testing process. Experiments demonstrate that the proposed algorithm is able to detect stegosystems as LSB-based embedding (both replacing and matching), with pseudorandom walks given by stego-keys, and with matrix embedding based on Hamming codes with reasonable reliability.

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Acknowledgments

Authors thank Mr. M. Tokareva for assistance in some calculations.

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Correspondence to Guillermo Morales-Luna .

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Korzhik, V., Fedyanin, I., Godlewski, A., Morales-Luna, G. (2017). Steganalysis Based on Statistical Properties of the Encrypted Messages. In: Rak, J., Bay, J., Kotenko, I., Popyack, L., Skormin, V., Szczypiorski, K. (eds) Computer Network Security. MMM-ACNS 2017. Lecture Notes in Computer Science(), vol 10446. Springer, Cham. https://doi.org/10.1007/978-3-319-65127-9_23

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  • DOI: https://doi.org/10.1007/978-3-319-65127-9_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65126-2

  • Online ISBN: 978-3-319-65127-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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