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Steganalysis of JPEG Images with Joint Transform Features

  • Zohaib Khan
  • Atif Bin Mansoor
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5414)

Abstract

In this paper, a universal steganalysis scheme for JPEG images based upon joint transform features is presented. We first analyzed two different transform domains (Discrete Cosine Transform and Discrete Wavelet Transform) separately, to extract features for steganalysis. Then a combination of these two feature sets is constructed and employed for steganalysis. A Fisher Linear Discriminant classifier is trained on features from both clean and steganographic images using all three feature sets and subsequently used for classification. Experiments performed on images embedded with two variants of F5 and Model based steganographic techniques reveal the effectiveness of proposed steganalysis approach by demonstrating improved detection for joint features.

Keywords

Steganography Steganalysis Information Hiding Feature Extraction Classification 

References

  1. 1.
    Johnson, N.F., Jajodia, S.: Exploring Steganography: Seeing the Unseen. IEEE Computer 31(2), 26–34 (1998)CrossRefGoogle Scholar
  2. 2.
    Simmons, G.J.: Prisoners’ Problem and the Subliminal Channel. In: CRYPTO 1983-Advances in Cryptology, pp. 51–67 (1984)Google Scholar
  3. 3.
    Kharrazi, M., Sencar, T.H., Memon, N.: Benchmarking Steganographic and Steganalysis Techniques. In: Proc. of SPIE Electronic Imaging, Security, Steganography and Watermarking of Multimedia Contents VII, San Jose, California, USA (2005)Google Scholar
  4. 4.
    Fridrich, J., Goljan, M., Hogea, D.: Steganalysis of JPEG images: Breaking the F5 Algorithm. In: Proc. 5th International Workshop on Information Hiding, Noordwijkerhout, The Netherlands, pp. 310–323 (October 2002)Google Scholar
  5. 5.
    Aboalsamh, H.A., Dokheekh, S.A., Mathkour, H.I., Assassa, G.M.: Breaking the F5 Algorithm: An Improved Approach. Egyptian Computer Science Journal 29(1), 1–9 (2007)Google Scholar
  6. 6.
    Westfeld, A., Pfitzmann, A.: Attacks on Steganographic Systems. In: Proc. 3rd Information Hiding Workshop, Dresden, Germany, pp. 61–76 (1999)Google Scholar
  7. 7.
    Fridrich, J., Goljan, M., Hogea, D.: Attacking the OutGuess. In: Proc. ACM Workshop on Multimedia and Security 2002. ACM Press, Juan-les-Pins (December 2002)Google Scholar
  8. 8.
    Avcibas, I., Memon, N., Sankur, B.: Image Steganalysis with Binary Similarity Measures. In: Proc. of the IEEE International Conference on Image Processing, Rochester, New York (September 2002)Google Scholar
  9. 9.
    Farid, H.: Detecting Hidden Messages Using Higher-order Statistical Models. In: Proc. of the IEEE International Conference on Image Processing, vol. 2, pp. 905–908 (2002)Google Scholar
  10. 10.
    Fridrich, J.: Feature-Based Steganalysis for JPEG Images and its Implications for Future Design of Steganographic Schemes. In: Moskowitz, I.S. (ed.) Information Hiding 2004. LNCS, vol. 2137, pp. 67–81. Springer, Heidelberg (2005)Google Scholar
  11. 11.
    Avcibas, I., Memon, N., Sankur, B.: Steganalysis Using Image Quality Metrics. IEEE Transactions on Image Processing 12(2), 221–229 (2003)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Wang, Y., Moulin, P.: Optimized Feature Extraction for Learning-Based Image Steganalysis. IEEE Transactions on Information Forensics and Security 2(1) (2007)Google Scholar
  13. 13.
    Schaefer, G., Stich, M.: UCID - An Uncompressed Colour Image Database. In: Proc. SPIE, Storage and Retrieval Methods and Applications for Multimedia, San Jose, USA, pp. 472–480 (2004)Google Scholar
  14. 14.
    UCID – Uncompressed Colour Image Database (visited on 02/08/08), http://vision.cs.aston.ac.uk/datasets/UCID/ucid.html
  15. 15.
    Steganography Software F5 (visited on 02/08/08), http://wwwrn.inf.tu-dresden.de/~westfeld/f5.html
  16. 16.
    Westfeld, A.: F5 – A Steganographic Algorithm: High capacity despite better steganalysis. In: Moskowitz, I.S. (ed.) 4th International Workshop Information Hiding. LNCS, pp. 289–302. Springer, Heidelberg (April 2001)CrossRefGoogle Scholar
  17. 17.
    Model Based JPEG Steganography Demo (visited on 02/08/08), http://www.philsallee.com/mbsteg/index.html
  18. 18.
    Sallee, P.: Model Based Steganography. In: International Workshop on Digital Watermarking, Seoul, Korea, pp. 174–188 (October 2003)Google Scholar
  19. 19.
    Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification, 2nd edn. John Wiley & Sons, New York (2001)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Zohaib Khan
    • 1
  • Atif Bin Mansoor
    • 1
  1. 1.College of Aeronautical EngineeringNational University of Sciences & TechnologyPakistan

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