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Robust Steganography Using Texture Synthesis Based on LBP

  • Weiyi Wei
  • Chengfeng AEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 895)

Abstract

In order to improve the embedded capacity and anti-interference capability of the coverless steganography algorithm, this paper proposes a texture synthesis information hiding method based on LBP texture analysis. Firstly, selects the original texture image and divides it into uniform pixel blocks, calculates the LBP value of each pixel in an image block and takes the LBP value with the largest LBP distribution as the information represented for the image block. Secondly, the pseudo-random sequence is generated with specified key to determine the position of the texture candidate block placed on the white paper, then select the candidate block based on the value of the secret message and place it on the designated position on the white paper, meanwhile, the remaining blank areas are filled with texture synthesis method. Inversely, during the procedure of extracting the secret message, the position of the steganography image block is obtained according to the pseudo-random sequence generated by the customary key, and then the LBP value of each image block with the largest distribution is calculated to obtain secret information. Experimental results show that the constructed stego-image has good visual effects, more embedded capacities and robustness to some interference.

Keywords

LBP Texture synthesis Steganography Coverless information hiding 

Notes

Acknowledgement

This work was supported by National Natural Science Foundation of China (Grant 61762080), Science and Technology Plan of Gansu Province (17YF1FA119).

References

  1. 1.
    Shen, C.X., Zhang, H.G., Feng, D.G.: A survey of information security. Chinese Science. Sci. China 37(2), 129–150 (2007)Google Scholar
  2. 2.
    Wang, H., Wang, S.: Cyber warfare: steganography vs. steganalysis. Commun. ACM 47(10), 76–82 (2004)CrossRefGoogle Scholar
  3. 3.
    Fridrich, J., Goljan, M.: Practical steganalysis of digital images: state of the art. In: Security and Watermarking of Multimedia Contents IV Security and Watermarking of Multimedia Contents IV, pp. 1–13 (2002)Google Scholar
  4. 4.
    Fridrich, J.: Asymptotic behavior of the ZZW embedding construction. IEEE Trans. Inf. Forensics Secur. 4(1), 151–154 (2009)CrossRefGoogle Scholar
  5. 5.
    Zhang, W., Wang, X.: Generalization of the ZZW embedding construction for steganography. IEEE Trans. Inf. Forensics Secur. 4(3), 564–569 (2009)CrossRefGoogle Scholar
  6. 6.
    Xu, D.H., Zhu, C.Q., Wang, Q.S.: A construction of digital watermarking model for the vector geospatial data based on magnitude and phase of DF. J. Beijing Univ. Posts Telecommun. 34(5), 25–28 (2011)Google Scholar
  7. 7.
    Cox, I.J., Kilian, J., Leighton, F.T.: Secure spread spectrum watermarking for multimedia. Secur. Spread Spectr. Watermark. Images Audio Video 3, 243–246 (1997)Google Scholar
  8. 8.
    Hsieh, M.S., Tseng, D.C., Huang, Y.H.: Hiding digital watermarks using multiresolution wavelet transform. IEEE Trans. Industr. Electron. 48(5), 875–882 (2010)CrossRefGoogle Scholar
  9. 9.
    Pevny, T., Fridrich, J.: Merging Markov and DCT features for multi-class JPEG steganalysis. In: Proceedings of SPIE - The International Society for Optical Engineering, pp. 650503-650503-13 (2007)Google Scholar
  10. 10.
    Shi, Y.Q., Chen, C., Chen, W.: A markov process based approach to effective attacking JPEG steganography. In: Information Hiding, International Workshop, IH 2006, Alexandria, VA, USA, 10–12 July 2006. Revised Selected Papers DBLP, pp. 249–264 (2006)Google Scholar
  11. 11.
    Lyu, S., Farid, H.: Steganalysis using higher-order image statistics. IEEE Trans. Inf. Forensics Secur. 1(1), 111–119 (2006)CrossRefGoogle Scholar
  12. 12.
    Pevny, T., Bas, P., Fridrich, J.: Steganalysis by subtractive pixel adjacency matrix. In: ACM Workshop on Multimedia and Security, pp. 75–84. ACM (2009)Google Scholar
  13. 13.
    Fridrich, J., Kodovsky, J.: Rich models for steganalysis of digital images. IEEE Trans. Inf. Forensics Secur. 7(3), 868–882 (2012)CrossRefGoogle Scholar
  14. 14.
    Efros, A.A., Freeman, W.T.: Image quilting for texture synthesis and transfer. In: Proceedings of SIGGRAPH, pp. 341–346 (2001)Google Scholar
  15. 15.
    Ashikhmin, M.: Synthesizing natural textures. In: Symposium on Interactive 3d Graphics, pp. 217–226. ACM (2001)Google Scholar
  16. 16.
    Kwatra, V.: Texture optimization for example-based synthesis. In: ACM SIGGRAPH, pp. 795–802. ACM (2005)Google Scholar
  17. 17.
    Dong, F., Ye, X.: Multiscaled texture synthesis using multisized pixel neighborhoods. IEEE Comput. Graph. Appl. 27, 41–47 (2007)Google Scholar
  18. 18.
    Otori, H., Kuriyama, S.: Data-embeddable texture synthesis. In: Smart Graphics, International Symposium, SG 2007, Kyoto, Japan, 25–27 June 2007, Proceedings DBLP, pp. 146–157 (2007)Google Scholar
  19. 19.
    Otori, H., Kuriyama, S.: Texture synthesis for mobile data communications. IEEE Comput. Graph. Appl. 29(6), 74–81 (2009)CrossRefGoogle Scholar
  20. 20.
    Cohen, M.F., Shade, J., Hiller, S., Deussen, O.: Wang tiles for image and texture generation. ACM Trans. Graph. 22(3), 287–294 (2003)CrossRefGoogle Scholar
  21. 21.
    Xu, K.: Feature-aligned shape texturing. In: ACM SIGGRAPH Asia, p. 108. ACM (2009)Google Scholar
  22. 22.
    Wu, K.C., Wang, C.M.: Steganography using reversible texture synthesis. IEEE Trans. Image Process. 24(1), 130–139 (2015)MathSciNetCrossRefGoogle Scholar
  23. 23.
    Qian, Z., et al.: Robust steganography using texture synthesis. In: Advances in Intelligent Information Hiding and Multimedia Signal Processing. Springer, Cham (2017)Google Scholar
  24. 24.
    Zhou, Z., Yu, C., Sun, X.: The coverless information hiding based on image bag-of-words model. J. Appl. Sci. 34(5), 527–536 (2016)Google Scholar
  25. 25.
    Yan, Y.K.: 2D Image Texture Synthesis Techniques Based on LBP. Hebei Normal University (2009)Google Scholar

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.College of Computer Science and EngineeringNorthwest Normal UniversityLanzhouChina

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