2. Definition & Classification

Transcription

1 Information Hiding Data Hiding K-H Jung Agenda 1. Data Hiding 2. Definition & Classification 3. Related Works 4. Considerations

2 Definition of Data Hiding 3 Data Hiding, Information Hiding Concealing secret messages within other innocuous information Digital images, audio, video, etc Concealing their existence Encryption Secure method of communication Protecting the contents of messages 4 Embeds data into digital media for the purpose of identification, annotation and copyright Cover Image Secret Data Stego Image (Image, Text,...)

3 Hierarchical Classification 5 Embedding Model 6

4 Category of Data Hiding 7 Irreversible Least Significant Bit (LSB) Substitution Pixel-Value l Differencing i (PVD) Reversible Recovery of the original image by extracting the embedded information from the stego- image Distortion-free, lossless, invertible Histogram Shifting Difference Expansion (DE) 1. Least Significant Bit Substitution p p Cover image - gray : 1pixel = 8bits (value : 0 ~ 255)... Secret Data : p p irreversible

5 2. Pixel-Value Differencing 9 Embedding algorithm Range table Range F = ( P, P ) = (50, 61) i (, i x) (, i y) di = P(, i y) P(, i x) = = 11 d ' i ' l j + ti for d 0 = + < ' ( l j ti) for d 0 l t = log( w ) j R 1 = [0,7] R 2 = [8,15] R 3 = [16,31] R 4 = [32,63] R 5 = [64,127] R 6 = [128,255] Secret message u j w j t i = 5 10 = = 13 i j m = d - d = = 2 irreversible 10 Embedding algorithm d i = 11 ' ' P(, ix) m/ 2, P(, iy) + m/ 2 for odd di ( P(, ix), P(, iy) ) = P m/ 2, P + m/ 2 for even d Recall: (, ix) (, iy) i ( P, P ) = (50, 61) m = 2 (, i x) (, i y) = (49, 62) Extracting algorithm d = P P = = 13 ' ' ' i (, i y) (, i x) Range table ' ' = Range l j u j w j ti log( wj) ' di lj for di 0 ti = = 13-8 = 5 ' ' d for 0 R 1 = [0,7] i lj di < 10 R 2 = [8,15] R 3 = [16,31] Extracted Secret message R 4 = [32,63] R 5 = [64,127] R 6 = [128,255]

6 1. by Histogram Shifting Cover image Peak point, a=3 Zero point, b=6 Count secret bits Stego image Pixel value Peak point Zero point reversible 2. Using a Difference Expansion 12 Embedding (x, y) = l = = = 203, h= = h' = 2 h+ b= = x' = = 209, y' = 203 = Extracting 5 = 101 (2) 5 2 = 1010(2) = l' = l : it integer average between bt two pixels 203, = h = = h : difference value between two pixels h' b= LSB( h') = 1, h= = 5 b : secret bit 2 h x= l + = = h 5 y = l = = (2) reversible

7 Basic Measurement 13 Visual Quality PSNR (Peak Signal to Noise Ratio) PSNR = 10 x log / MSE M-1 N-1 MSE = (p(x,y) - p'(x,y)) 2 / M x N x=0 y=0 Quality Index Capacity 1. 가변길이자료은닉이가능한이미지스테가노그래픽방법 14 Motives Fall-off the boundary problem Wu and Tsai s s Pixel-Value Differencing (PVD) Chang and Tseng s Side-Match Method

8 Review of Pixel-value Differencing 15 가변길이자료은닉이가능한이미지스테가노그래픽방법 Review of Two Side-match Method 16 가변길이자료은닉이가능한이미지스테가노그래픽방법

9 Fall-off the Boundary Problem 17 가변길이자료은닉이가능한이미지스테가노그래픽방법 Fall-off the Boundary Problem 18 Case 1. d = (g u + g l ) / 2 - g x > 1 가변길이자료은닉이가능한이미지스테가노그래픽방법

10 Fall-off the Boundary Problem 19 Case 2. d = (g u + g l ) / 2 - g x < 1 가변길이자료은닉이가능한이미지스테가노그래픽방법 Proposed Method 20 d 0 가변길이자료은닉이가능한이미지스테가노그래픽방법

11 Proposed Method 21 d <0 가변길이자료은닉이가능한이미지스테가노그래픽방법 2. 이진이미지에대한픽셀값가중치를이용한자료은닉기법연구 22 Motives Hiding data in binary image is more challenging than any other formats Two primary methods for binary images Sub-block block modification Single pixel manipulation

12 Proposed Method 23 A sub-block of cover Weighted Value w w x = (1x0 + 2x1 + 1x1) + (-1x1 + -2x0 + -1x0) = (-1) = 2 y = (-1x0 + -2x0 + -1x1) + (1x1 + 2x1 + 1x0) = = 2 w2 = x + y = = 4 이진이미지에대한픽셀값가중치를이용한자료은닉기법연구 24 Additional Topics

13 Application in Military 25 Military and intelligence agencies require unobtrusive communications. Even if the content is encrypted, the detection of a signal on a modern battlefield may lead rapidly to an attack on the signaller. For this reason, military communications use techniques such as spread spectrum modulation or meteor scatter transmission to make signals hard for the enemy to detect or jam Spread spectrum radio techniques have been developed for military applications since the mod-1940 s because of their antijamming and low-probability-of-intercept properties R. C. Dixon, Spread spectrum systems with commercial applications, New York, John Wiley & Sons, 1994 R. A. Scholtz, The origins of spread spectrum communcations, IEEE Transactions on Communications, Vol. 30, No. 5, pp , 1982 R. L. Pickholtz, D. L. Schilling, L. B. Milstein, Theory of spread spectrum communications a tutorial, IEEE Transactions on Communications, Vol. 30., No. 5, pp , 1982 Data Hiding Using Image Interpolation 26 Computer Standards & Interfaces, vol. 31, pp , 2009

14 Data Hiding Using Run Length Matching 27 Matching Case International Journal of Intelligent Information and Database Systems, 28 Non-matching Case International Journal of Intelligent Information and Database Systems,

15 Data Hiding Method with Quality Control lf for Binary Images 29 Embedding Journal of Software Engineering and Applications, pp.20-24, Extracting Journal of Software Engineering and Applications, pp.20-24,

16 Improved Exploiting Modification Direction i Method by Modulus Operation 31 Embedding International Journal of Signal Processing, Image Processing and Pattern, pp.79-88, Extracting International Journal of Signal Processing, Image Processing and Pattern, pp.79-88,

17 Experiments 33 Considerations 34 IBM 11 ~ 12 pages Elsevier 25 ~ 30 pages Abstract 4 sentences Abstract 1 paragraph Introduction 1 page Introduction 1.5 ~ 2 manuscript pages Problem 1 page Methods 2 ~ 4 pages My idea 2 pages Results & Discussion 10 ~ 12 pages The details 5 pages Conclusions 1 ~ 2 pages Related work Conclusion & further work 1~2 pages 0.5 page Remark : o double space, 12 pt o Figures 6~8 Tables 1~3 References 20~50 items