Cover
Vol. 8 No. 1 (2012)

Published: November 30, 2012

Pages: 1-11

Original Article

Partial Encryption of Compressed Image Using Threshold Quantization and AES Cipher

Abstract

Cryptography is one of the technological means to provide security to data being transmitted on information and communication systems. When it is necessary to securely transmit data in limited bandwidth, both compression and encryption must be performed. Researchers have combined compression and encryption together to reduce the overall processing time. In this paper, new partial encryption schemes are proposed to encrypt only part of the compressed image. Soft and hard threshold compression methods are used in the compression step and the Advanced Encryption Standard (AES) cipher is used for the encryption step. The effect of different threshold values on the performance of the proposed schemes are studied. The proposed partial encryption schemes are fast, secure, and do not reduce the compression performance of the underlying selected compression methods.

References

  1. Cheng H., Partial Encryption for Thesis, Department of Computing Science, University of Alberta, Alberta, 1998.
  2. Borie J., Puech W., Dumas M., “Crypto-Compression System for Secure Transfer of Medical Images”, 2 nd Medical Signal and Processing (MEDSIP 2004), September 2004.
  3. Uehara T., Safavi-Naini R., Ogunbona P., “Securing Wavelet Compression with Random Permutations”, In Proceedings of the 2000 IEEE Pacific Rim Conference on Multimedia, pp. 332-335, Sydney, 2000.
  4. Usevitch B. E., “A Tutorial on Modern Lossy Wavelet Compression: Foundations of JPEG 2000”, IEEE Transactions on Image Processing Magazine, September 2001.
  5. Li X., Knipe J., Cheng H., “ Image Compression and Encryption Using Tree Structures ”, Pattern Recognition Letters, Vol. 18, No. 11-13, pp. 1253-1259, 1997.
  6. Norcen R., Podesser M., Pommer A., Schmidt H., Uhl A., “Confidential Storage and Transmission of Medical Image Data”, Computers Biology and Medicine 33, pp. 277-292, 2003.
  7. Younis, H. A., New Techniques For Partial Encryption of Wavelet-based Compressed and Uncompressed Images , Ph.D. Thesis, Department of Computer Science, College of Science, University of Basrah, Basrah, November 2006.
  8. National Institute of Standards and Technology, FIPS-197-Advanced Encryption Standard (AES), November 2001.
  9. Stallings W., Cryptography and Network Security, Principles and Practice, Third Edition, Pearson Education
  10. Antonini M., Barlaud M, Daubechies “Image Coding Using Wavelet Transform”, IEEE Transactions on Image Processing, Vol. 1, No. 2, pp. 1716-1740, April 1992.
  11. Baxes A., Digital Processing: Principles and Applications, John Wiley & Sons, Inc., USA, 1994.
  12. Gonzalez R. C., Woods R. E., Digital USA, 1992.
  13. Saha S., “Image Compression-From DCT to Wavelet: A Review”, ACM Crossroads Student Magazine, The ACM’s First Electronic Publication, 2001.
  14. Tang L., “ Methods for Encryption and Decryption MPEG Video Data Efficiently”, Proceedings of the Fourth ACM International Conference on Multimedia, pp. 219-229, 1997.
  15. Xiong Z., Ramchandran K., Orchard M. T., Zhang Y., “A Comparative Study of DCT-and Wavelet-Based Image Coding”, Transactions on Circuits and Systems for Video Technology, Vol. 9, No. 5, August 1999.
  16. Usevitch B. E., “A Tutorial on Modern Lossy Wavelet Compression: Foundations of JPEG 2000”, IEEE Transactions on Image Processing Magazine, September 2001.
  17. DeVore R. A., Jawerth B., Lucier B. J., “Image Compression Through Wavelet Transform Coding”, IEEE Trans. on Info. Theory, Vol. 38, No. 2, pp. 719-746, 1992.
  18. Beegan A. P., Wavelet-based Image Compression Using Human Visual System Models, M.Sc. Thesis, Electrical Engineering Department, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, May 2001.
  19. Salomon D., Data Compression, The Complete Reference, Springer-Verlag, Inc., New York, 1998.