Key-Based Scrambling for Secure Image Communication

  • Prashan Premaratne
  • Malin Premaratne
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 304)


Secure image communication is becoming increasingly important due to theft and manipulation of its content. Law enforcement agents may find it increasingly difficult to stay afloat above the ill intentions of hackers. We have been able to develop an image scrambling algorithm that is very simple to implement but almost impossible to breach with a probability less than 5x10− 300. This is possible due to the fact that a user may purchase or acquire rights for an intended image by specifying a ‘key’ that can form a sequence of numbers 10 to 100 in length. The content provider uses this sequence as a base in developing another key sequence to scramble the image and transmit it to the user through regular channels such as an email attachment. Since the user is the only party apart from the provider to possess the key for descrambling, any third party will not be able to descramble it successfully as will be shown in this paper.


Image scrambling image communication image shuffling key generation 


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  1. 1.
    Renesse, R.L.: Hidden and Scrabbled Images- a Review. In: Conference on Optical Security and Counterfeit Deterence Techniques IV, vol. 4677, pp. 333–348. SPIE (2002)Google Scholar
  2. 2.
    Huang, H.: An Image Scrambling Encryption Algorithm Combined Arnold and Chaotic Transform. In: Int. Conf. China Communication, pp. 208–210 (2010)Google Scholar
  3. 3.
    Fang, L., YuKai, W.: Restoring of the Watermarking Image in Arnold Scrambling. In: 2nd International Conference on Signal Processing Systems (ICSPS), pp. 771–774 (2010)Google Scholar
  4. 4.
    Liu, Z., Chen, H., Liu, T., Li, P., Xu, L., Dai, J., Liu, S.: Image Encryption by Us-ing Gyrator Transform and Arnold Transform. Journal of Electronic Imaging 20(1) (2011)Google Scholar
  5. 5.
    Kong, T., Zhang, D.: A New Anti-Arnold Transformation Algorithm. Journal of Software 15(10), 1558–1564 (2004)MathSciNetzbMATHGoogle Scholar
  6. 6.
    Zhou, Y., Joyner, V.M., Panetta, K.: Two Fibonacci P-code Based Image Scram-bling Algorithms. Image Processing: Algorithms and Systems VI 6812, 681215, 1–12 (2008)Google Scholar
  7. 7.
    Che, S., Che, Z., Ma, B.: An Improved Image Scrabbling Algorithm. In: Proc. Second Int. Conf. Genetics and Evolutionary Computing, pp. 495–499 (2008)Google Scholar
  8. 8.
    Fridrich, J.: Image Encryption Based on Chaotic Maps. In: Proc. IEEE Conf. Systems, Man, and Cybernetics, pp. 1105–1110 (1997)Google Scholar
  9. 9.
    Yeo, J., Guo, C.: Efficient Hierarchical Chaotic Image Encryption Algorithm and Its VLSI Realisation. In: IEE Proceedings Vision, Image and Signal Processing, vol. 147(2), pp. 167–175 (2000)Google Scholar
  10. 10.
    Liping, S., Zheng, Q., Bo, L., Jun, Q., Huan, L.: Image Scrambling Algorithm Based on Random Shuffling Strategy. In: 3rd IEEE Conference on Industrial Electronics and Applications, vol. 4677, pp. 2278–2283. SPIE (2008)Google Scholar
  11. 11.
    Ville, D., Philips, W., Walle, R., Lemahieu, I.: Image Scrambling Without Band-width Expansion. IEEE Trans. Circ. Sys. Video Tech. 14(6), 892–897 (2004)Google Scholar
  12. 12.
    Liu, S., Sheridan, J.T.: Optical Information Hiding by Combining Image Scrambling Techniques in Fractional Fourier Domains. In: Irish Signal and Systems Conference, pp. 249–254 (2001)Google Scholar
  13. 13.
    Zhou, Y., Panetta, K., Agaian, S.: An Image Scrambling Algorithm Using Parameter Based M-sequence. In: Proc. Seventh Inter. Conf. Mach. Learning and Cybern., pp. 3695–3698 (2008)Google Scholar
  14. 14.
    Gu, G., Han, G.: The Application of Chaos and DWT in Image Scrambling. In: Proceedings of the Fifth International Conference on Machine Learning and Cybernetics, pp. 3729–3373 (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Prashan Premaratne
    • 1
  • Malin Premaratne
    • 2
  1. 1.School of Electrical Computer and Telecommunications EngineeringUniversity of WollongongNorth WollongongAustralia
  2. 2.Department of Electrical and Computer Systems EngineeringMonash UniversityVictoriaAustralia

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