Abstract
Adaptive steganography methods tend to increase the security against attacks. Most of adaptive methods use LSB flipping (LSB-F) for embedding part of their algorithms. LSB-F is very much vulnerable against simple steganalysis methods but it allows the adaptive algorithms to be extractable at the receiver side. Use of LSB matching (LSB-M) could increase the security but extraction of data at the receiver is difficult or, in occasions, impossible. There are numerous attacks against LSB-M. In this paper we are proposing an adaptive algorithm which, unlike most adaptive methods, uses LSB-M as its embedding method. The proposed method uses a complexity measure based on a local neighborhood analysis for determination of secure locations of an image. Comparable adaptive methods that use LSB-M suffer from possible changes in the complexity of pixels when embedding is performed. The proposed algorithm is such that when a pixel is categorized as complex at the transmitter and is embedded the receiver will identify it as complex too, and data is correctly retrieved. Better performance of the algorithm is shown by obtaining higher PSNR values for the embedded images with respect to comparable adaptive algorithms. The security of the algorithm against numerous attacks is shown to be higher than LSB-M. Also, it is compared with a recent adaptive method and is proved to be advantageous for most embedding rates.
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References
Cancelli G, Cox IJ, Doerr G (2008) Improved LSB matching steganalysis based on the amplitude of local extrema, in IEEE International Conference on Image Processing, October
Cancelli G, Doerr G, Cox IJ, Barni M (2008) A comparative study of +1 steganalyzers, IEEE Int. Workshop. on Multimedia Signal Processing, IEEE Workshop on Multimedia Signal Processing, (MMSP)
Chang CC, Tseng HW (2004) A Steganographic method for digital images using side match. Pattern Recogn Lett pp. 1431–1437
Chen P, Wu W (2009) A Modified Side Match Scheme for Image Steganograph. International Journal of Applied Science and Engineering, pp. 53–60
Dumitrescu S, Wu X, Wang Z (2003) Detection of LSB Steganography via sample pair analysis. IEEE Trans Signal Process 51(7):1995–2007
Goljan M, Fridrich J, Holotyak T (2006) New blind steganalysis and its implications. In Security, Steganography, and Watermarking of Multimedia Contents VIII, ser. Proceedings of SPIE, Vvol. 6072, pp. 607 201–1
Harmsen JJ, Pearlman WA (2003) Steganalysis of Additive Noise Modelable Information Hiding, Proc. SPIE Electronic Imaging, Security, Steganography, and Watermarking of Multimedia Contents, Vol. 5020, pp. 131–142
Huang F, Li B, Huang J (2007) Attack LSB matching steganography by counting alteration rate of the number of neighbourhood gray levels. Proc IEEE ICIP 1:401–404
Ker AD (2005) Steganalysis of LSB matching in grayscale images. IEEE Signal Process Lett 12(6):441–444
Li X, Yang B, Cheng D, Zeng T (2009) A generalization of LSB matching. IEEE Signal Process Lett 16(2):69–72
Liu TC, Huang CC (2007) Lossless Information Hiding Scheme Based on Pixels Complexity Analysis, Proceedings of Third International Conference on Signal Image Technology & Internet-based Systems (SITIS 2007), Shanghai, China, pp. 934–941
Liu C, Li X, Lu X, Yang B (2009) A content-adaptive approach for reducing embedding impact in steganography. In Proc IEEE ICIP
Luo W, Huang F, Huang J (2010) Edge adaptive image steganography based on LSB matching revisited. IEEE Trans Inform Forens Sec 5(2):201–214
Maniccam SS, Bourbakis N (2004) Lossless compression and information hiding in images. Pattern Recogn 37:475–486
Mielikainen J (2006) LSB matching revisited. IEEE Signal Process Lett 13(5):285–287
Omoomi M, Samavi S, Dumitrescu S (2010) An efficient high payload ±1 data embedding scheme. J Multimed Tool Appl 54(2):201–218
Sabeti V, Samavi S, Mahdavi M, Shirani S (2007) Steganalysis of pixel-value differencing steganographic method. IEEE Pacific Rim Conference on Communications, Computers and Signal Processing, pp. 292–295
Sabeti V, Samavi S, Mahdavi M, Shirani S (2010) Steganalysis and payload estimation of embedding in pixel differences using neural networks. Pattern Recogn 43:405–415
United States Department of Agriculture (2002) Natural resources conservation service photo gallery. [Online]. Available: http://photogallery.nrcs.usda.gov
Wu DC, Tsai WH (2003) A steganographic method for images by pixel-value differencing. Pattern Recognit Lett 24:1613–1626
Yang CH, Weng CY, Wang SJ, Sun HM (2008) Adaptive data hiding in edge areas of images with spatial LSB domain systems. IEEE Trans Inform Forens Sec 3(3):488–497
Zhang J, Cox IJ, Doerr G (2007) Steganalysis for LSB matching in images with high-frequency noise. In Proceedings of the IEEE Workshop on Multimedia Signal Processing, pp. 385–388, October
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Sabeti, V., Samavi, S. & Shirani, S. An adaptive LSB matching steganography based on octonary complexity measure. Multimed Tools Appl 64, 777–793 (2013). https://doi.org/10.1007/s11042-011-0975-y
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DOI: https://doi.org/10.1007/s11042-011-0975-y