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Genetic Algorithm Based Steganography Using Wavelets

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Information Systems Security (ICISS 2007)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 4812))

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Abstract

Steganography has long been a means of secure communication. Security is achieved by camouflaging the secret message. In this paper, we present a Genetic Algorithm based Steganography using Discrete Cosine Transforms(GASDCT) and Genetic Algorithm based Steganography using Discrete Wavelets Transform(GASDWT). In our approach, the Discrete Cosine Transform and Discrete Wavelet Transform are applied to the payload. Genetic Algorithm is used to generate many stego-images based on Fitness functions; one of these which give least statistical evidence of payload is selected as the best stego image to be communicated to the destination. It is observed that GASDWT has an improvement in Bit Error Rate(BER), Peak Signal to Noise Ratio(PSNR) and embedding capacity as compared to GASDCT.

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References

  1. Wu, Y.-T., Shih, F.Y.: Genetic Algorithm based Methodology for Breaking the Steganalytic Systems. IEEE Transactions on Systems, Man and Cybernetics 36 (Feburary 2006)

    Google Scholar 

  2. Ji, R., Yao, H., Liu, S., Wang, L.: Genetic Algorithm based Optimal Block Mapping Method for LSB Substitution. In: IIHP-MSP 2006. Proceedings of the International Information Hiding and Multimedia Signal Processing, pp. 215–218 (2006)

    Google Scholar 

  3. Luke, S., Spector, L.: A Comparison of Crossover and Mutation in Genetic Programming. In: GP 1997. Proceedings of the Second Annual Conference on Genetic Programming (1997)

    Google Scholar 

  4. Solanki, K., Sullivan, K., Manjunath, B.S., Chandrasekhran, S.: Provably Secure Steganography: Achieving Zero k-l Divergence using Statistical Restoration. In: Proceedings on IEEE International Conference on Image Processing, USA, pp. 125–128 (2006)

    Google Scholar 

  5. Amin, M.F., Mohammad, R., Akbarzadeh, T., Farshad, V.-A.: A New Genetic Algorithm Approach for Secure JPEG Steganography, pp. 22–23 (April 2006)

    Google Scholar 

  6. Tong, L., Zheng-ding, Q.: A DWT based Color Image Steganography Scheme. In: Proceedings of the Sixth International Conference on Signal Processing, vol. 2, pp. 1568–1571 (August 2002)

    Google Scholar 

  7. Chang, C.-C., Chen, T.-s., Hsia, H.-C.: An Effective Image Steganographic Scheme based on Wavelet Transformation and Pattern based Modification. In: ICCNMC 2003. Proceedings of the International Conference on Computer Networks and Mobile Computing, pp. 450–453 (October 2003)

    Google Scholar 

  8. Sung, A.H., Tadiparthi, G.R., Srinivas, Mukkamala: Defeating the Current Steganalysis Techniques (Robust Steganography). In: ITCC 2004. IEEE Proceedings of the International Conference on Information Technology: Coding and Computing (2004)

    Google Scholar 

  9. Chu, R., You, X., Kong, X., Ba, X.: A DCT-based Image Steganographic Method Resisting Statistical Attacks. In: ICASSP 2004. IEEE transaction, Acoustic, Speech and Signal Processing, vol. 5, pp. 953–956 (May 2004)

    Google Scholar 

  10. Westfeld, A., Pfitzmann, A.: Attacks on Steganographic Systems Breaking the Steganographic Utilities EzStego, Jsteg, Steganos, and S-Tools and Some Lessons Learned. In: Pfitzmann, A. (ed.) IH 1999. LNCS, vol. 1768, pp. 61–76. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  11. Chandramouli, R.: Data Hiding Capacity in the Presence of an Imperfectly known Channel. In: SPIE. Proceedings of Security and Watermarking of Multimedia, vol. 2 (2001)

    Google Scholar 

  12. Sallee, P.: Model-Based Methods for Steganagraphy and Steganalysis. International Journal of Image and Graphics 5(1), 167–189 (2005)

    Article  Google Scholar 

  13. Campisi, P., Kundur, D., Hatzinakos, D., Neri, A.: Compressive Data Hiding: An Unconventional Approach for improved Color Image Coding. Journal on Applied Signal Processing EURASIP, 152–163 (2002)

    Google Scholar 

  14. Anderson, R.J., Peticolas, F.A.P.: On the Limits of Steganography. IEEE journal on selected areas in Communications 16, 474–481 (1998)

    Article  Google Scholar 

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Patrick McDaniel Shyam K. Gupta

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© 2007 Springer-Verlag Berlin Heidelberg

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Raja, K.B. et al. (2007). Genetic Algorithm Based Steganography Using Wavelets. In: McDaniel, P., Gupta, S.K. (eds) Information Systems Security. ICISS 2007. Lecture Notes in Computer Science, vol 4812. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77086-2_5

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  • DOI: https://doi.org/10.1007/978-3-540-77086-2_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77085-5

  • Online ISBN: 978-3-540-77086-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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