Multimedia Data Hiding

Transcription

1 Multimedia Data Hiding Introduction! Digital Watermarking / Multimedia Data Hiding Hide secondary data in digital image/video/audio/3d! Uses of hidden data: ownership verification, alteration detection access control, annotation, side info. delivery Min Wu Dept. of Electrical Engineering Committee: Profs. B.Liu, P.Ramadge, S.Kulkarni! Issues and challenges: imperceptibility, robustness & security, capacity tradeoff between the conflicting requirements Robustness Imperceptibility Capacity 2 General Framework Key Elements of Data Hiding 1111 Hello, World original media data to be hidden extracted 1111 data Hello, World player embed play/ record/ extract marked media (w/ hidden data) compress process / attack! Perceptual model! Embedding one bit! Multiple bits! Uneven embedding capacity! Robustness and security! What data to embed Upper Layers security error correction uneven capacity equalization Physical Layer how to embed one or multiple bits? 3 4 1

2 Thesis Outline " Fundamental issues and solutions # embedding strategy classification and capacity issues # handling uneven capacity # modulation/multiplexing techniques for hiding multiple bits " Algorithm and system designs # binary images # image authentication # video copy/access control and fingerprinting # applications in video communication " Attacks and countermeasures # innocent tools block replacement and double-capturing # countermeasure against rotation/scale/translation # robustness & security analysis on SDMI audio watermarking Algorithm and System Designs " Demonstrating solutions to fundamental issues 5 6 Data Hiding in Binary Image Example-1: Signature in Signature! A simple yet important class of images scanned documents, drawings, signatures! Challenges E-PAD (InterLink Electronics) little room for invisible changes uneven distribution of changeable pixels Clinton electronically signed Electronic Signatures Act - Yahoo News 6/3/ media/gif/bil.gif as of 7/ 7 Annotating digitized signature with content info. of the signed document (Finkelstein - Princeton U.) 8 2

3 Our Approach! Block-based pixel-domain method hide a fixed number of bits in each block extract hidden data without the use of original copy Robustness is not a major requirement for authentication and annotation applications. Preserve Visual Quality! Assign flippability score to each pixel determine how noticeable the flipping of a pixel is based on smoothness and connectivity Hierarchical! Three issues determine which pixels to flip for invisibility embed data in each block using flippable pixels handle uneven embedding capacity via shuffling (a) (b)! Sort pixels in each block according to the scores flip high-score pixels with high priority 9 1 Embedding Mechanism! Extracting data without original image hard to directly encode data in flippable pixels # flippability may change after encoding! Our approach manipulate flippable pixels to enforce block-based property # enforce the total number of black pixels to be odd/even to hide 1 bit / block, or use more general mapping # incorporate quantization or tolerance zone for robustness # of black pixel per blk 2kQ (2k+1)Q (2k+2)Q (2k+3)Q odd-even mapping 1 1 lookup table mapping Shuffling for Binary Image! Uneven distribution of flippable pixels most are on rugged boundary! Embedding rate (per block) variable: need side info. constant: require larger blk! Random shuffling equalizes distribution embed more bits enhance security portion of blocks Important! Pixels with high flippability score are shown in the images. image size 288x48, red block size 16x16 before shuffle after shuffle embeddble coeff. # per block (signature img) 12 3

4 Analysis of Shuffling Compare Analysis with Simulation for Shuffling Mean follows hypergeometric distribution m /N ( th bin) m 1/N (1 st bin) m 2/N (2 nd bin) before shuffle 2.37% 1.85% 5.56% mean after shuffle analysis simulation 5.16x1-5 % % 7.77x1-4 % % 5.81x1-3 % 5.56x1-3 % std after shuffle analysis simulation 9.78x x m r ~ # of blocks each having r blue balls out of q balls q balls... pick w/o replacement N = S/q blocks portion of blocks (x 1%) before shuffle before shuff simulation mean simulation std analytic mean analytic std mean after shuffle std after shuffle q = 16 x 16 S = 288 x 48 N = S/q = 18 x 3 p = 5.45%.5 unchangeable pixel/coeff. changeable pixel/coeff. S balls in total n = ps blue balls 13 Simulation: 1 indep. random shuff # of flippable pixels per block (signature img) 14 Example-1: Signature in Signature Each block is 32- pixel large, 1bit / blk. Example-2: Document Authentication (c) (a) alter (d) (f) (b) after alteration (e) (g) Annotating digitized signature with content info. of the signed document (Finkelstein - Princeton U.) 15 Embed pre-determined pattern or content features beforehand Verify hidden data s integrity to decide on authenticity 16 4

5 Robustness vs. Capacity! Blind/non-coherent detection ~ original copy unavailable! Single robustness-capacity setting over-estimates and/or under-estimates actual noise not all embedded data are equally important Robustness Capacity Capacity C (bits/ch. use) Capacity of Type-I (host=1e) and Type-II AWGN ch. (wmk MSE E 2 ) Type-I (C-i C-o, blind detection) Type-II (D-i D-o) grayscale/color image/video Experimental Results 6-frame 352 x 24 flower garden sequence 66-frame 352 x 24 concatenated sequence Level-1: high capacity Level-2: high robustness embed. rate robustness embed. rate robustness 64 bits (91 char.) 332 bits avg. chunk size = 6 frames Video Examples MPEG-2 4.5Mbps; frame dropping 132 bits (18 char.) 1266 bits MPEG-2 1.5Mbps; frame dropping Notes also embed control info. Imperceptibility log 1 (E 2 /σ 2 ) (db) stronger noise weaker Video Example Robust Video Data Hiding embed b i & (i mod M) embed b i+1 & (i+1 mod M) 1st & 3th Mpeg4.5Mbps frame of original, marked, and their luminance difference human visual model for imperceptibility: protect smooth areas and sharp edges 19! Embedding domain partition video into segments of similar consecutive frames for each frame of a segment, embed same data in block-dct domain embed segment index to detect frame jitter! Multi-level embedding light processing data extractable from just a few frames severe processing extractable by processing more frames! Uneven embedding capacity seg. i seg. i+1 within a frame: constant embedding rate per region & shuffling between frames: embed # of hidden bit per frame as side info.! Modulation/Multiplexing techniques TDMA, CDMA, orthogonal/bi-orthogonal modulation 2 5

6 Watermark Attacks: What and Why? Attacks & Countermeasures! Attacks: intentionally obliterate watermarks remove a robust watermark make watermark undetectable (e.g., miss synchronization) uncertainty in detection (e.g., multiple ownership claims) forge a valid (fragile) watermark bypass watermark detector 21! Why study attacks? identify weaknesses propose improvement understand pros and limitation of tech. solution To win each campaign, a general should know both his troop and the opponent s as well as possible. -- Sun Tzu, The Art of War, 5 B.C. 22 Innocent Tools Used by Attackers! Recovery of lost blocks for resilient multimedia transmission of JPEG/MPEG good quality by edge-directed interpolation: Jung et al; Zeng-Liu! Remove robust watermark by block replacement JPEG 1% marked original (no distortion) after proposed attack edge estimation edge-directed interpolation JPEG 1% w/o distort Interp. w/ orig w/o orig x512 lenna Threshold: 3 ~ 6! Attack effective on block-dct based spread-spectrum watermark 23 claimed high robustness&quality by fine tuning wmk strength for each region 24 6

7 Secure Digital Music Initiative Challenge SDMI Challenge Setup Obtained From SDMI Job for Attackers Black Box (unknown)! International consortium ~ 18+companies/organizations currently pursuing watermark based solution for access and copy control on digital music Sample-1 (original) Watermark (special signal) Embed Sample-2 (marked)! Public challenge ( 9/15-1/8/2 ) attacks on four robust watermark technologies Any Marked Audio Detect Watermark Found! Non-traditional research values reveal real industrial problem and state-of-art technologies present an emulated rivalry environment for better understanding on audio watermarking lead to a few research problems Sample-3 (marked) Attack Sample-4 (attacked) Detect GOAL Watermark NOT Found Observation on One SDMI Watermark Difference between original and marked samples given by SDMI 27 Learning from SDMI Challenge! Our successful attacks blind attacks: warping, jittering attacks based on studying orig.-marked pairs # deliberate filtering / subtraction / randomization! Noteworthy issues duality between embedding and attacks secrecy of embedding can t rely on orig. being unknown double-watermarking used by SDMI # robust wmk should resist processing/attacks # fragile wmk indicate audio experience compression attacks and countermeasures on forging fragile wmk # relate to watermark-based authentication 28 7

8 Is Watermark Useful?! Not an answer to all our attacks pointed out weaknesses of specific proposals and demonstrated general approaches! For copy/access control hard to get complete solution with technology alone # business model, pricing model, etc. Summary improved watermark tech. could be part of the solution # make attack non-trivial and keep honest people honest! Other applications detecting alteration # digital camera/camcorder; digitized signature/ binary doc. convey side information # for performance enhancement or additional funtionality 29 3 Summary & Conclusion! Data hiding in digital multimedia for a variety of purposes, involving multiple disciplines! Tradeoff among many criterions! Important to think both as designer and as attacker! Data hiding in market digital cameras with authentication watermark module plug-in for image editors video watermark proposals for DVD copy control on-going SDMI effort for digital music Digital Rights Management (DRM) for multimedia data 31 Other Data Hiding Works in Thesis! Watermark-based image/video authentication, attack & countermeasures hide auth. data via look-up table in quantized coeff. (ICIP 98 & 99) double capturing attack and countermeasure (Asilomar 99)! Rotation/Scale/Translation resilient watermarking (w/ NECI) add spread-spectrum wmk in log-polar of FFT magnitude (Trans. IP 1, SPIE )! Data hiding for video communication (w/ P. Yin) real-time video transcoding via downsizing # send subblock motion for better visual quality error concealment # protect motion vectors by embedding parity bits 32 8

9 Publication List Fundamental Issues 1. M. Wu, B. Liu: Data Hiding in Images and Videos: Part I Fundamental Issues and Solutions, draft, to be submitted to IEEE Trans. on Circuits & Systems for Video Technology, Feb M. Wu, H. Yu, A. Gelman: Multi-level Data Hiding for Digital Image and Video, SPIE M. Wu, B. Liu: Digital Watermarking Using Shuffling, IEEE ICIP'99. Designs 1. C-Y. Lin, M. Wu, Y-M. Lui, J.A. Bloom, M.L. Miller, I.J. Cox: Rotation, Scale, and Translation Resilient Public Watermarking for Images, to appear in IEEE Transactions on Image Processing, May M. Wu, B. Liu: Data Hiding in Binary Images, submitted to IEEE Trans. on Multimedia, Apr M. Wu, H. Yu, B. Liu: Data Hiding in Images and Videos: Part II Designs and Applications, draft, to be submitted to IEEE Trans. on Circuits & Systems for Video Technology, Feb M. Wu, B. Liu: Data Hiding for Image and Video Authentication, to be submitted to IEEE Trans. on Image Processing, Jan M. Wu, E. Tang, B. Liu: Data Hiding in Digital Binary Image, IEEE ICME'. 6. M. Wu, H. Yu: Video Access Control via Multi-level Data Hiding, IEEE ICME'. 7. P. Yin, M. Wu, B. Liu: Video Transcoding by Reducing Spatial Resolution, IEEE ICIP. 8. C-Y. Lin, M. Wu, J.A. Bloom, M.L. Miller, I.J. Cox, and Y-M. Lui: Rotation, Scale, and Translation Resilient Public Watermarking for Images, SPIE (list of design papers - cont d) 9. M. Wu, B. Liu: Watermarking for Image Authentication, ICIP' P. Yin, M. Wu, B. Liu: Error Concealment for MPEG Video Over Internet, submitted to ICIP 1. Attacks & Countermeasures 1. M. Wu, S. Craver, E. Felten, B. Liu: Analysis of Attacks on SDMI Audio Watermarks, to appear in IEEE ICASSP'1. 2. S. Craver, P. McGregor, M. Wu, B. Liu, A. Stubblefield, B. Swartzlander, D.S. Wallach, D. Dean, E.W. Felten: Reading Between the Lines: Lessons from the SDMI Challenge, to appear in 4 th Info. Hiding Workshop, M. Wu, B. Liu, Attacks on Digital Watermarks, Asilomar 99. Non-watermark Works on Video (not included in thesis) 1. M. Wu, R. Joyce, H-S. Wong, L. Guan, S-Y. Kung: Dynamic Resource Allocation Via Video Content and Short-term Traffic Statistics, to appear in IEEE Trans. on Multimedia, special issues on multimedia over IP, June M. Wu, R. Joyce, S-Y. Kung: Dynamic Resource Allocation Via Video Content and Short-term Traffic Statistics, ICIP, invited paper. 3. H-S. Wong, M. Wu, R. Joyce, L. Guan, S-Y. Kung: A Neural Network Approach For Predicting Network Resource Requirement in Video Transmission, IEEE Pacific Rim Conference on Multimedia (PCM ). 4. M. Wu, W. Wolf, B. Liu, "An Algorithm of Wipe Detection", IEEE ICIP' Questions? Comments? Welcome! Acknowledgement Prof. Bede Liu (advisor) Dr. Wenjun Zeng (HVS and error concealment) Prof. Adam Finkelstein, Ed Tang, Mishella Yoshi (binary image) Dr. Heather Yu (multilevel data hiding) PengYin (transcoding and error concealment) Scott Craver, Prof. Ed Felten (SDMI attacks) Drs. I. Cox, M. Miller, J. Bloom, H. Stone (data hiding & RST wmk) 35 9