Journal of Real-Time Image Processing

, Volume 14, Issue 1, pp 87–99 | Cite as

Portable real-time DCT-based steganography using OpenCL

  • Ante PoljicakEmail author
  • Guillermo Botella
  • Carlos Garcia
  • Luka Kedmenec
  • Manuel Prieto-Matias
Special Issue Paper


In this paper, a steganographic method for real-time data hiding is proposed. The main goal of the research is to develop steganographic method with increased robustness to unintentional image processing attacks. In addition, we prove the validity of the method in real-time applications. The method is based on a discrete cosine transform (DCT) where the values of a DCT coefficients are modified in order to hide data. This modification is invisible to a human observer. We further the investigation by implementing the proposed method using different target architectures and analyze their performance. Results show that the proposed method is very robust to image compression, scaling and blurring. In addition, modification of the image is imperceptible even though the number of embedded bits is high. The steganalysis of the method shows that the detection of the modification of the image is unreliable for a lower relative payload size embedded. Analysis of OpenCL implementation of the proposed method on four different target architectures shows considerable speedups.


Steganography Real-time OpenCL GPU Parallel processing 


  1. 1.
    Alvarez, P.: Using extended file information (EXIF) file headers in digital evidence analysis. Int. J. Digit. Evid. 2(3), 1–5 (2004)MathSciNetGoogle Scholar
  2. 2.
    AMD (2015a) AMD A series APU processors,15.6.2015.
  3. 3.
    AMD (2015b) AMD Radeon HD 8670d, 15.6.2015.
  4. 4.
    Bamatraf, A., Ibrahim, R., Salleh, M.N.B.M.: Digital watermarking algorithm using LSB. In: 2010 International Conference on Computer Applications and Industrial Electronics, IEEE, Iccaie, pp. 155–159 (2010). doi: 10.1109/ICCAIE.2010.5735066,
  5. 5.
    Bhatnagar, G., Raman, B.: A new robust reference watermarking scheme based on DWT-SVD. Comput. Stand. Interfaces 31(5), 1002–1013 (2009). doi: 10.1016/j.csi.2008.09.031,
  6. 6.
    Celik, M., Sharma, G., Tekalp, A., Saber, E.: Lossless generalized-LSB data embedding. In: IEEE Transactions on Image Processing 14(2), 253–266 (2005). doi: 10.1109/TIP.2004.840686,
  7. 7.
    Cheddad, A., Condell, J., Curran, K., Mc Kevitt, P.: Digital image steganography: Survey and analysis of current methods. Signal Process. 90(3), 727–752 (2010). doi: 10.1016/j.sigpro.2009.08.010.
  8. 8.
    Cox, I., Miller, M., Bloom, J., Fridrich, J., Kalker, T.: Digital Watermarking and Steganography, 2nd edn. Morgan Kaufmann Publishers, San Francisco (2008)Google Scholar
  9. 9.
    CUDA (2016) CUDA toolkit documentation-sample reference.
  10. 10.
    Dey, S., Abraham, A., Sanyal, S.: An LSB data hiding technique using prime numbers. In: Third International Symposium on Information Assurance and Security, IEEE 1, 101–108 (2007). doi: 10.1109/IAS.2007.37.
  11. 11.
    Dosselmann, R., Yang, X.D.: A comprehensive assessment of the structural similarity index. SIViP 5(1), 81–91 (2011). doi: 10.1007/s11760-009-0144-1 CrossRefGoogle Scholar
  12. 12.
    Groups, K.: OpenCL Consortium. (2016)
  13. 13.
    Hashad, A., Madani, A., Wahdan, A.M.a.: A robust steganography technique using discrete cosine transform insertion. In: 2005 International Conference on Information and Communication Technology, IEEE, Cairo, pp. 255–264 (2005). doi: 10.1109/ITICT.2005.1609628.
  14. 14.
    Kang, X., Huang, J., Member, S., Zeng, W.: Efficient general print-scanning resilient data hiding based on uniform log-polar mapping. In: IEEE Transactions on Information Forensics and Security 5(1), 1–12 (2010). doi: 10.1109/TIFS.2009.2039604.
  15. 15.
    Kedmenec, L., Poljicak, A., Mandic, L.: Copyright protection of images on a social network. In: Proceedings ELMAR-2014, IEEE, September, pp. 1–4 (2014). doi: 10.1109/ELMAR.2014.6923345.
  16. 16.
    Kee, E., Johnson, M.K., Farid, H.: Digital image authentication from JPEG headers. In: IEEE Transactions on Information Forensics and Security 6(3), 1066–1075 (2011). doi: 10.1109/TIFS.2011.2128309.
  17. 17.
    Kodovský, J., Fridrich, J., Holub, V.: Ensemble classifiers for steganalysis of digital media. IEEE Trans. Inf. Forensics Secur. 7(2), 432–444 (2012). doi: 10.1109/TIFS.2011.2175919 CrossRefGoogle Scholar
  18. 18.
    Kurak, C., McHugh, J.: A cautionary note on image downgrading. In: 1992 Proceedings Eighth Annual Computer Security Application Conference, IEEE Comput. Soc. Press, pp. 153–159 (1992). doi: 10.1109/CSAC.1992.228224.
  19. 19.
    Lu, W., Sun, W., Lu, H.: Robust watermarking based on DWT and nonnegative matrix factorization. Computers & Electrical Engineering 35(1), 183–188 (2009). doi: 10.1016/j.compeleceng.2008.09.004.
  20. 20.
    Naveed, I., Puech, W.: Data cryptography. In: Naït-Ali, A., Fournier, R. (eds.) Signal and image processing for biometrics. Wiley, Hoboken, pp. 263–277 (2013). doi: 10.1002/9781118561911.ch13.
  21. 21.
    Parthasarathy, A., Kak, S.: An Improved method of content based image watermarking. IEEE Trans. Broadcast. 53(2), 468–479 (2007). doi: 10.1109/TBC.2007.894947.
  22. 22.
    Pevny, T., Fridrich, J.: Merging Markov and DCT features for multi-class JPEG steganalysis. Proc SPIE 6505(650), 503 (2007). doi: 10.1117/12.696774.
  23. 23.
    Poljicak, A., Mandic, L., Agic, D.: Discrete fourier transformbased watermarking method with an optimal implementation radius. J. Electron. Imaging 20(3):033,008 (2011). doi: 10.1117/1.3609010. \(\{\)&\(\}\)Agg=doi
  24. 24.
    Scarpino, M.: OpenCL in Action: How to Accelerate Graphics and Computation. NY (2012)Google Scholar
  25. 25.
    Schneier, B.: Applied Cryptography: Protocols, Algorithm, and Source Code in C, 2nd edn. Wiley, New York (1995)zbMATHGoogle Scholar
  26. 26.
    Shi, Y., Chen, C., Chen, W.: A Markov process-based approach to effective attacking JPEG steganography. Inf. Hiding, pp. 249–264 (2007). doi: 10.1007/978-3-540-74124-4.
  27. 27.
    Sung, T., Shieh, Y., Yu, C., Hsin, H.: High-efficiency and low-power architectures for 2-d dct and idct based on cordic rotation. In: Seventh International Conference on Parallel and Distributed Computing, Applications and Technologies, 2006. PDCAT ’06, pp. 191–196 (2006). doi: 10.1109/PDCAT.2006.70
  28. 28.
    Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600–612 (2004). doi: 10.1109/TIP.2003.819861 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.University of ZagrebZagrebCroatia
  2. 2.Complutense University of MadridMadridSpain

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