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2017 | OriginalPaper | Chapter

Image Modelling: A Feature Detection Approach for Steganalysis

Authors : Anuj Rani, Manoj Kumar, Payel Goel

Published in: Advances in Computing and Data Sciences

Publisher: Springer Singapore

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Abstract

The most popular challenges in steganalysis is to identify the characterstics, to discover the stego-images. In this, we derive a steganalysis measure using Gaussian distribution, for image modeling. By using Gaussian distribution model the distribution of DCT coefficients and quantify a ratio of two Fourier coefficients of the distribution of DCT coefficients [9]. This derive steganalysis measure is evaluated against three steganographic methods i.e. first one is LSB (Least Significant Bit), the second one is SSIS (Spread Spectrum Image Steganography), and the last one is Steg-Hide tool, which is based on graph theoretic approach. Classification of image features dataset is done by using different classification techniques such as SVM.

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previous chapter Hybrid Segmentation Technique Using Wavelet Packet and Watershed Transform for Medical Images
next chapter Implementation of Medical Image Watermarking Technique Using FPGA
Literature
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Adhiya, K.P., Patil, S.A.: Hiding text in audio using LSB based steganography. Inf. Knowl. Manag. 2(3), 8–15 (2012)
2.
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Avcibas, I., Menon, N., Sankur, B.: Steganalysis using image quality metrics. IEEE Trans. Image Process. 12(2), 221–229 (2003)MathSciNetCrossRef
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Fridrich, J.: Feature-based steganalysis for JPEG images and its implications for future design of steganographic schemes. In: Fridrich, J. (ed.) IH 2004. LNCS, vol. 3200, pp. 67–81. Springer, Heidelberg (2004). doi:10.​1007/​978-3-540-30114-1_​6 CrossRef
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Dumitrescu, S., Wu, X., Wang, Z.: Detection of LSB steganography via sample pair analysis. IEEE Trans. Sig. Process. 51(7), 1999–2007 (2003)CrossRefMATH
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Hetzl, S., Mutzel, P.: A graph–theoretic approach to steganography. In: Dittmann, J., Katzenbeisser, S., Uhl, A. (eds.) CMS 2005. LNCS, vol. 3677, pp. 119–128. Springer, Heidelberg (2005). doi:10.​1007/​11552055_​12 CrossRef
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Bera, S., Sharma, M.: A review on blind still image steganalysis techniques using features extraction and pattern classification method. IJCSEIT 2(3), 117–135 (2012)CrossRef
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Gonzalez, F.P., Heileman, G.L., Quanch, T.T.: Model-based steganalysis using invariant features. In: Media Forensics and Security. Proceedings of SPIE, vol. 7254, p. 72540B, 4 February 2009. doi:10.​1117/​12.​810507
Metadata
Title
Image Modelling: A Feature Detection Approach for Steganalysis
Authors
Anuj Rani
Manoj Kumar
Payel Goel
Copyright Year
2017
Publisher
Springer Singapore
Book
Advances in Computing and Data Sciences

Print ISBN: 978-981-10-5426-6

Electronic ISBN: 978-981-10-5427-3

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-981-10-5427-3_15

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