Analysis of chi-squared divergence changes by filtering of stego images formed according to UNIWARD embedding methods

Authors

Keywords:

steganalysis, adaptive embedding methods, UNIWARD algorithm, chi-squared divergence

Abstract

Counteraction to sensitive information leakage is topical task today. Special interest is taken on early detection of hidden (steganographic) information transferring by data transmission in communication systems. Message (stego data) embedding is provided by alteration of cover files, such as digital images, according to used steganographic algorithm. Reliable detection of formed stego images requires usage of targeted stegdetector that needs a priori information about specific distortions (signatures) of cover due to data hiding. It makes detection systems vulnerable to zero-day attack – usage by malefactors the previously unknown embedding algorithms. Therefore it is required development of universal (blind) stegdetectors that are capable to reliable revealing of stego images even in case of limited or absence information about used embedding method.

Creation of blind stegdetector requires determination of cover image parameters that are sensitive to any alteration caused by message hiding. As such parameters it is proposed to use information-theoretic estimations (chi-square divergence) of pixels brightness distribution distortion due to stego data embedding. For amplification of these distortions it is used image pre-processing with median and Wiener filters. The case of adaptive messages hiding in cover images according to UNIWARD methods is considered. It is revealed that usage of chi-square divergence allows reliably detection of small alteration of cover image even in case of low cover payload (less than 10\%). Different character of chi-square divergence changes for filtered images by information hiding in spatial and JPEG domains allows determine type of used embedding domain.

Author Biography

D. O. Progonov, National Technical University of Ukraine "Igor Sikorsky Kyiv Politechnic Institute"

Progonov D. O., Cand. of Sci(Techn), Assoc. Prof.

References

Fridrich J. (2009) Steganography in Digital Media. DOI: 10.1017/cbo9781139192903

Kodovský J. and Fridrich J. (2012) Steganalysis of JPEG images using rich models. Media Watermarking, Security, and Forensics 2012. DOI: 10.1117/12.907495

Fridrich J. and Kodovsky J. (2012) Rich Models for Steganalysis of Digital Images. IEEE Transactions on Information Forensics and Security, Vol. 7, Iss. 3, pp. 868-882. DOI: 10.1109/tifs.2012.2190402

Holub V., Fridrich J. and Denemark T. (2014) Universal distortion function for steganography in an arbitrary domain. EURASIP Journal on Information Security, Vol. 2014, Iss. 1. DOI: 10.1186/1687-417x-2014-1

Davidson J., Bergman C. and Bartlett E. (2005) An artificial neural network for wavelet steganalysis. Mathematical Methods in Pattern and Image Analysis. DOI: 10.1117/12.615280

Progonov D. (2018) Information-Theoretic Estimations of Cover Distortion by Adaptive Message Embedding. Information Theories and Applications, Vol. 25, No 1, pp. 47-62.

Filler T. and Fridrich J. (2010) Gibbs Construction in Steganography. IEEE Transactions on Information Forensics and Security, Vol. 5, Iss. 4, pp. 705-720. DOI: 10.1109/tifs.2010.2077629

Bishop C. (2006) Pattern Recognition and Machine Learning, Springer-Verlag, 738 p.

Kodovsky J., Fridrich J. and Holub V. (2012) Ensemble Classifiers for Steganalysis of Digital Media. IEEE Transactions on Information Forensics and Security, Vol. 7, Iss. 2, pp. 432-444. DOI: 10.1109/tifs.2011.2175919

Huiskes M.J. and Lew M.S. (2008) The MIR flickr retrieval evaluation. Proceeding of the 1st ACM international conference on Multimedia information retrieval - MIR '08. DOI: 10.1145/1460096.1460104

Avcibas I., Memon N. and Sankur B. (2003) Steganalysis using image quality metrics. IEEE Transactions on Image Processing, Vol. 12, Iss. 2, pp. 221-229. DOI: 10.1109/tip.2002.807363

Gonzalez R.C and Woods R. E. (2007) Digital Image Processing, Prentice Hall, 976 p.

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Published

2019-03-30

How to Cite

Progonov, D. O. (2019) “Analysis of chi-squared divergence changes by filtering of stego images formed according to UNIWARD embedding methods”, Visnyk NTUU KPI Seriia - Radiotekhnika Radioaparatobuduvannia, 0(76), pp. 72-76. Available at: https://radap.kpi.ua/radiotechnique/article/view/1553 (Accessed: 21November2024).

Issue

No. 76 (2019)

Section

Information Security

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