Abstract
Existing model-preserving steganography techniques are based on embedding data by modifying least significant bits of a cover image. To keep invariant component of pixel intact only, Least Significant Bit Replacement (LSBR) function is used to modify non-invariant component of the pixel. LSBR is found to be weak against visual or statistical attacks and provide limited steganographic capacity. Least significant Bit Matching (LSBM) embedding provides better security in comparison LSBR but it is not suitable for most of the model-preserving steganographic techniques. This paper explores the possibility of securely embedding data in least two significant bits of the cover image. It is shown that the embedding in least two significant bits violates the assumption of the structural steganalysis tools and techniques available to detect presence of a message in a stego image. Therefore, structural and non-structural detectors fail to detect presence of data in a stego image. The proposed embedding functions result in improved security and steganographic capacity in comparison to LSBM.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Westfeld, A.: F5-A Steganographic Algorithm. In: Moskowitz, I.S. (ed.) IH 2001. LNCS, vol. 2137, pp. 289–302. Springer, Heidelberg (2001)
Mielikainen, J.: LSB matching revisited. IEEE Signal Processing Letters 13(5), 285–287 (2006)
Fridrich, J.J., Kodovský, J.: Rich Models for Steganalysis of Digital Images. IEEE Transactions on Information Forensics and Security 7(3), 868–882 (2012)
Pevný, T., Fridrich, J.J., Ker, A.D.: From Blind to Quantitative Steganalysis. IEEE Transactions on Information Forensics and Security 7(2), 445–454 (2012)
Provos, N., Honeyman, P.: Hide and seek: an introduction to steganography. IEEE Transactions on Security Privacy 1(3), 32–44 (2003)
Upham, D.: Jsteg (2013), ftp://ftp.funet.fi/pub/crypt/steganography/
Fridrich, J.J., Pevný, T., Kodovský, J.: Statistically Undetectable JPEG Steganography: Dead ends Challenges, and Opportunities. In: The 9th Workshop on Multimedia & Security (MM&Sec), Dallas, Texas, USA, pp. 3–14. ACM (2007)
Filler, T., Judas, J., Fridrich, J.: Minimizing Additive Distortion in Steganography using Syndrome-Trellis Codes. IEEE Transactions on Information Forensics and Security 6(3), 920–935 (2011)
Cox, I.J., Miller, M.L., Bloom, J.A., Fridrich, J., Kalker, T.: Digital Watermarking and Steganography, 2nd edn. Morgan Kaufmann (2008)
Lee, K., Westfeld, A., Lee, S.: Category Attack for LSB steganalysis of JPEG images. In: Shi, Y.Q., Jeon, B. (eds.) IWDW 2006. LNCS, vol. 4283, pp. 35–48. Springer, Heidelberg (2006)
Dumitrescu, S., Wu, X., Memon, N.: On steganalysis of random LSB embedding in continuous-tone images. In: International Conference on Image Processing, Rochester, New York, USA, vol. 3, pp. 641–644 (2002)
Ker, A.D., Böhme, R.: Revisiting weighted stego-image steganalysis. In: Electronic Imaging, Security, Forensics, Steganography, and Watermarking of Multimedia Contents X, SPIE, Orlando, Florida, USA, vol. 6819, pp. 5:1–5:17 (2008)
Pevný, T., Bas, P., Fridrich, J.: Steganalysis by subtractive pixel adjacency matrix. In: 11th ACM Workshop on Multimedia and Security, MM&Sec, New York, USA, pp. 75–84 (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Islam, S., Gupta, P. (2014). Extended Embedding Function for Model-Preserving Steganography. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theory. ICIC 2014. Lecture Notes in Computer Science, vol 8588. Springer, Cham. https://doi.org/10.1007/978-3-319-09333-8_88
Download citation
DOI: https://doi.org/10.1007/978-3-319-09333-8_88
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09332-1
Online ISBN: 978-3-319-09333-8
eBook Packages: Computer ScienceComputer Science (R0)