An Innovative Steganographic Scheme Based on Vector Quantization

1. An Innovative Steganographic Scheme Based on Vector Quantization Chin-Chen Chang Chair Professor, Feng Chia University Honorary and Hopewell Appointed Professor, National Chung Cheng University Hopewell Appointed Professor, National Tsing Hua University http://msn.iecs.fcu.edu.tw/~ccchttp://msn.iecs.fcu.edu.tw

2. Introduction • Images have been widely used in our daily life. • The image security has become an important issue in current computer world. • Image cryptology is a very useful tool to defend the information security.

3. Apply the Traditional Cryptosystem on Images Cipher Image Decrypted Image Original Image encryption decryption

4. Problems • The cipherimage is meaningless. Image Camouflage • Image size is huge Image Compression • The decrypted image containing a small distortion is usually acceptable. Vector Quantization

5. Virtual Image Cryptosystem Original Image Advantages: • camouflage • security • compression • acceleration Decrypted Image Cipher Image Virtual Image encryption decryption

6. VQ Encoding (120,155,…,80) 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 (90,135,…,120) (100,125,…,150) … Index table Original Image (49,117,…,25) (50,42,…,98) (20,65,…,110) Codebook How to get a good codebook?

7. LBG Algorithm • Step 1: x0 x1 . . . Dividing the images into vectors x59997 X59998 x59999 Training Images Training vectors set

8. LBG Algorithm • Step 2: x0 X1 . . . x73 x342 . . . Randomly choose 256 initial code-vectors 256 code- vectors x24312 x49810 x59997 x59998 x59999 Initial codebook Training vectors set

9. {x5, x5431, … } {x1, x306, … } . . . {x67, x822, … } LBG Algorithm • Step 3: Vector-groups 0 1 . . . x0 X1 . . . 254 255 x59997 x59998 x59999 Codebook The set of training vectors = {x0, x1, … , x59999} Join the closest code-vectors, and to form 256 vector-groups.

10. {x5, x5431, …} {x1, x306, … } 0 1 . . . . . . {x67, x822, …} 254 255 LBG Algorithm • Step 4: Vector-groups Compute mean value of each group, replace the old code-vectors New Codebook Go to Step3 to repeat training until the total distortion has stabilized. Chang, C. C. and Lin, C. Y., (2007): "Density-Based Image Vector Quantization Using a Genetic Algorithm," The Proceedings of 13th International MultiMedia Modelling Conference (MMM2007), (Cham, T. J., Cai, J., Dorai, C., Rajan, D., Chua, T. S. and Chia, L. T. Eds.), Springer Verlag, Part I, Singapore, Jan. 2007, pp. 289-298.

11. The Principle of the Virtual Image Cryptosystem • Separate O into a set of vectors {O1, O2, O3,…, Ono}. • Separate V into another set of vectors {V1, V2, V3, … , Vnv}. • Let O be the original image. • Let {V1, V2, V3, …, Vnv} be the codebook.

12. Encryption • Randomly generate the transformed-origin G and the project-direction D. • Project {V1, V2, V3, …, Vnv} to D based on G. • Sort the projected results, and obtain {V’1, V’2, V’3, …, V’nv}.

14. Encrypt w, h, no, G, and D into wc, hc, noc, Gc, and Dc by DES-like, respectively. • Encrypt I into Ic, where Ic=IXORX and X is the bit-string containing G, D, G, D,… only. • Hide wc, hc, noc, Gc, Dc, and Ic into the pixels of V. Cipher Image Vc

15. Decryption

16. Empirical Tests-Test 1 Original Image Airplane 512 X 512

17. Empirical Tests-Test 1 Virtual Image Lena 256 X 256 Cipher Image Lena 256 X 256 PSNR=37.87dB

18. Empirical Tests-Test 1 Decrypted Image Airplane 512 X 512 PSNR=30.22dB

19. Empirical Tests-Test 2 Original Image Airplane 512 X 512

20. Empirical Tests-Test 2 Cipher Image Lena 360 X 360 PSNR=45.13dB Virtual Image Lena 360 X 360

21. Empirical Tests-Test 2 Decrypted Image Airplane 512 X 512 PSNR=31.36dB

22. Empirical Tests-Test 3 Original Image Peppers 512 X 512

23. Empirical Tests-Test 3 Cipher Image Lena 256 X 256 PSNR=37.60dB Virtual Image Lena 256 X 256

24. Empirical Tests-Test 3 Decrypted Image Peppers 512 X 512 PSNR=29.91dB