Abstract
An important property of any robust steganographic method is that it must introduce minimal distortion in the created stego-images. This objective is achieved if one can maximize the similarity between the pixels value of the cover image and the secret data. In the proposed framework, the maximal similarity is obtained by arranging some routes along the pixel positions. Our novel method is based on dynamic blocking and the genetic algorithm which decreases the distortion produced by a base data embedding method. In the proposed parametric framework, the cover image is first divided into several horizontal static-size strips. Then each strip is partitioned into some dynamic-size blocks. The size of each block is determined using the genetic algorithm such that minimal distortion is produced. Traversing the blocks of a strip in a raster scan manner, the route for embedding the data into the strip is obtained. The best route is considered to be the one which partition a strip into different blocks with different sizes. The embedding route is raster scan of the partitioned blocks. In our framework, only the sizes of the blocks need to be recorded as the overhead instead of the routes. The experimental results evaluated on 2000 natural images using several steganalytic algorithms demonstrate that our proposed method decreases the image distortion and thus enhances the security.
Similar content being viewed by others
References
Abolghasemi M, Aghaeinia H, Faez K, Mehrabi MA (2010) Detection of LSB ± 1 steganography based on co-occurrence matrix and bit plane clipping. J Electron Imaging 19(1):013014
Amirkhani H, Rahmati M (2011) New framework for using image contents in blind steganalysis systems. J Electron Imaging 20(1):013016
Amirtharajan R, Rayappan JBB (2012) An intelligent chaotic embedding approach to enhance stego-image quality. Inf Sci 193:115–124
Back T, Fogel DB, Michalewicz Z (2000) Evolutionary computation vol.2 - Advanced algorithms and operators. Institute of physics publishing, Bristol and Philadelphia
Chan CS (2010) On using LSB matching function for data hiding in pixels. Fundam Informaticae 96:49–59
Chan CK, Cheng LM (2004) Hiding data in images by simple LSB substitution. Pattern Recogn 37(3):469–474
Chang CC, Lin CJ (2011) LIBSVM: A library for support vector machines. ACM Trans. Intelligent Systems and Technology 2(3), 1–27 (software available at: http://www.csie.ntu.edu.tw/~cjlin/libsvm)
Chao RM, Wu HC, Lee CC, Chu YP (2009) A novel image data hiding scheme with diamond encoding. EURASIP J. Inf. Security, 1–9, Article ID 658047
Fakhredanesh M, Rahmati M, Safabakhsh R (2013) Adaptive image steganography using contourlet transform. J of Electronic Imaging 22(4):043007
Filler T, Fridrich J (2009) Fisher information determines capacity of epsilon-secure steganography. Proc 11th Int Hiding Work, Lect Notes in Comput Sci 5806:31–47
Fridrich J (2010) Steganography in digital media: principles, algorithms, and applications. Cambridge University Press, New York, USA
Fridrich J, Goljan M, Du R (2001) Reliable detection of LSB steganography in color and grayscale images. Proc. ACM Workshop on Multimedia and Security, Ottawa, CA, pp 27–30
Hong W, Chen TS (2012) A novel data embedding method using adaptive pixel pair matching. IEEE Trans Inf Forens Secur 7(1):176–184
Hsu CW, Chang CC, Lin CJ (2010) A practical guide to support vector classification. Dept. of Computer Science, National Taiwan University, Taiwan
Iranpour M (2013) Adaptive edge tracing steganography. Proc. 55th IEEE International Symposium ELMAR-2013, Zadar, Croatia, pp 27–30
Iranpour M (2013) A novel steganographic method based on edge detection and adaptive multiple bits substitution. Proc. 18th IEEE International Conference on Digital Signal Processing (DSP’13), Santorini, Greece, pp 1–6
Iranpour M (2013) LSB-based steganography using Hamiltonian paths. Proc. 9th IEEE International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP’13), Beijing, China
Iranpour M, Rahmati M (2013) A novel block-based steganographic method. Proc. 3rd IEEE International eConference on Computer and Knowledge Engineering (ICCKE 2013), Mashhad, Iran, pp 167–172
Iranpour M, Safabakhsh R (2014) Reducing the embedding impact in steganography using Hamiltonian paths and writing on wet paper. Multimed Tools Appl: 1–16, doi:10.1007/s11042-014-1921-6
Joseph L, Renjit JA, Kumar PM (2013) Dynamic programming based encrypted reversible data hiding in images. J Appl Secur and Res 8:467–476
Jung KH, Yoo KY (2012) Data hiding using edge detector for scalable images. Multimed Tools Appl: 1–14
Ker AD, Bohme R (2008) Revisiting weighted stego-image steganalysis. Proc. SPIE, EI, Security, Forensics, Steganography, Watermarking of Multimedia Contents X, vol. 6819, San Jose, CA, pp 1–17
Kharrazi M, Sencar HT, Memon N (2006) Performance study of common image steganography and steganalysis techniques. J Electron Imaging 15(4):041104
Kim C (2012) Data hiding by an improved exploiting modification direction. Multimed Tools Appl: 1–16
Lin GS, Chang YT, Lie WN (2010) A framework of enhancing image steganography with picture quality optimization and anti-steganalysis based on simulated annealing algorithm. IEEE Trans Multimedia 12(5):345–357
Luo W, Huang F, Huang J (2011) A more secure steganography based on adaptive pixel-value differencing scheme. Multimed Tools Appl 52:407–430
Mielikainen J (2006) LSB matching revisited. IEEE Signal Process Lett 13(5):285–287
Omoomi M, Samavi S, Dumitrescu S (2011) An efficient high payload ±1 data embedding scheme. Multimed Tools Appl 54(2):201–218
Qin C, Chang CC, Huang YH, Liao LT (2013) An inpainting-assisted reversible steganographic scheme using a histogram shifting mechanism. IEEE Trans Circ and Systems for Vi Technol 23(7):1109–1118
Qin C, Chang CC, Chiu YP (2014) A novel joint data-hiding and compression scheme based on smvq and image inpainting. IEEE Trans Image Process 23(3):969–978
Sabeti V, Samavi S, Shirani S (2013) An adaptive LSB matching steganography based on octonary complexity measure. Multimed Tools Appl 64(3):777–793
Sagan H (1994) Space-filling curves. Springer, New York
Schaefer G, Stich M (2004) UCID - An Uncompressed Color Image Database. Proc. SPIE, Storage and Retrieval Methods and Applications for Multimedia, San Jose, USA, pp. 472–480, (available at: http://homepages.lboro.ac.uk/~cogs/datasets/ucid/ucid.html)
Sharp T (2001) An implementation of key-based digital signal steganography. Proc inf hiding work 2137:13–26
Vapnik VN (1995) The nature of statistical learning theory. Springer, New York
Wang ZH, Chang CC, Li MC (2012) Optimizing least-significant-bit substitution using cat swarm optimization strategy. Inf Sci 192:98–108
Westfeld A (2013)BOWS2 image database. http://dud.inf.tu-dresden.de/~westfeld/rsp/rsp.html. Accessed 20 May 2013
Wu NI, Wu KC, Wang CM (2012) Exploring pixel-value differencing and base decomposition for low distortion data embedding. Appl Soft Comput 12:942–960
Xu H, Wanga J, Kim HJ (2010) Near-optimal solution to pair-wise LSB matching via an immune programming strategy. Inf Sci 180(8):1201–1217
Yang CH (2008) Inverted pattern approach to improve image quality of information hiding by LSB substitution. Pattern Recogn 41:2674–2683
Zhang X, Wang S (2006) Efficient steganographic embedding by exploiting modification direction. IEEE Comm Lett 10(11):781–783
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Iranpour, M., Rahmati, M. An efficient steganographic framework based on dynamic blocking and genetic algorithm. Multimed Tools Appl 74, 11429–11450 (2015). https://doi.org/10.1007/s11042-014-2237-2
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-014-2237-2