A novel secret image sharing scheme for true-color images with size constraint

1. A novel secret image sharing scheme for true-color images with size constraint Source: Information Sciences, Vol. 179, No. 19, Sep.2009,pp.3247-3254. Author: Tsai Du-Shiau, Horng Gwoboa, Chen Tzung-Her, Huang Yao-Te Article history: Received 2 August 2008 Received in revised form 21 May 2009 Accepted 29 May 2009 Advisor: Chih-Hung Lin Speaker: 趙家寬

2. Outline • Introduction • Review of related works • The proposed scheme • Experimental results • Discussion • Conclusions

3. Introduction(1/3) • Secret Image Sharing (SIS) • Distributing partial information, called shares • Two types of SIS • Lossless • Lossy • Function ; and .

4. Introduction(2/3) • Three main categories of SIS • VC-based(視覺密碼學) • VVSS-based (變異視覺式機密分享) • IM-based(插值方法)

5. Introduction(3/3) • Four guidelines to propose a new SIS scheme • Support 24-bit true-color image • Size of each share is slightly increased • Camouflage images for hiding secrets should be natural • Visual perception and image properties

6. Review of related works(1/7) • VC-based secret image sharing schemes (Proposed by Naor and Shamir)

7. Review of related works(2/7) • Characteristics • Perfectly secure • Decode secrets by visual systems with no cryptography knowledge and without performing cryptographic computation • Transparencies are meaningless • Size of each transparency is much larger than that of secret images

8. Review of related works(3/7) • VVSS-based secret image sharing schemes (Proposed by Chang et al.) • Give three n x m pixels image - C-color secret image S and two randomly chosen cover images O1 and O2 • Colors of S is stored in the Color Index Table (CIT) • Each pixel in O1 and O2 is expanded into minimized subpixels to obtain two camouflage images, O1’ and O2’

9. Review of related works(4/7) M satisfies : (3) (4)

10. Review of related works(5/7) Bit-level based SIS scheme (Proposed by Lukac and Plataniotis)

11. Review of related works(6/7) • PCA and FFN neural networks • Principal component analysis (PCA) • Color image compression scheme with hybrid neural network consisting of Sanger’s algorithm • (Proposed by Clausen and Wechsler)

12. Review of related works(7/7) • The neural network begins with initial A and learns/updates weights aij according to • A feed forward neural network trained with back propagation also begins with initial B and learns/updates weights bij according to

13. The proposed scheme(1/4) • Initial phase Two global weighted matrices A and B

14. The proposed scheme(2/4) • Encoding phase • Input: a true-color secret image X • Output: n camouflage images (11)

15. The proposed scheme(3/4) (12) (13)

16. The proposed scheme(4/4) • Decoding phase • Input: n camouflage images, global weighted matrix B, seed s • Output: true-color secret image X’

17. Experimental results

18. Discussion(1/2) • Support the 24-bit true-color secret image • Size constraint on shares • Quality improvement • Efficiency of bandwidth and storage space • Security enhancement • Low computational power

19. Discussion(2/2)