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Digital watermarking / Ingemar J. Cox ... [et al.].

By: Cox, I. J. (Ingemar J.).
Contributor(s): Miller, Matthew L | Bloom, Jeffrey A.
Material type: materialTypeLabelBookPublisher: San Diego, CA : Academic Press, 2001Description: xxv, 539 p. : ill. ; 24 cm. + hbk.ISBN: 1558607145 (alk. paper).Subject(s): WatermarksDDC classification: 676.28027
Contents:
Applications and Properties -- Models of watermarking -- Basic message coding -- Watermarking with side information -- Analyzing errors -- Using perceptual models -- Robust watermarking -- Watermark security -- Content authentication.

Enhanced descriptions from Syndetics:

Digital watermarking is a key ingredient to copyright protection. It provides a solution to illegal copying of digital material and has many other useful applications such as broadcast monitoring and the recording of electronic transactions. Now, for the first time, there is a book that focuses exclusively on this exciting technology. Digital Watermarking covers the crucial research findings in the field: it explains the principles underlying digital watermarking technologies, describes the requirements that have given rise to them, and discusses the diverse ends to which these technologies are being applied. As a result, additional groundwork is laid for future developments in this field, helping the reader understand and anticipate new approaches and applications.

Includes bibliographical references (pages 501-519) and index.

Applications and Properties -- Models of watermarking -- Basic message coding -- Watermarking with side information -- Analyzing errors -- Using perceptual models -- Robust watermarking -- Watermark security -- Content authentication.

Table of contents provided by Syndetics

  • Preface (p. xv)
  • Example Watermarking Systems (p. xix)
  • 1 Introduction (p. 1)
  • 1.1 Information Hiding, Steganography, and Watermarking (p. 3)
  • 1.2 History of Watermarking (p. 6)
  • 1.3 Importance of Digital Watermarking (p. 9)
  • 2 Applications and Properties (p. 11)
  • 2.1 Applications (p. 12)
  • 2.1.1 Broadcast Monitoring (p. 12)
  • 2.1.2 Owner Identification (p. 15)
  • 2.1.3 Proof of Ownership (p. 17)
  • 2.1.4 Transaction Tracking (p. 18)
  • 2.1.5 Content Authentication (p. 20)
  • 2.1.6 Copy Control (p. 22)
  • 2.1.7 Device Control (p. 25)
  • 2.2 Properties (p. 26)
  • 2.2.1 Embedding Effectiveness (p. 27)
  • 2.2.2 Fidelity (p. 27)
  • 2.2.3 Data Payload (p. 28)
  • 2.2.4 Blind or Informed Detection (p. 29)
  • 2.2.5 False Positive Rate (p. 29)
  • 2.2.6 Robustness (p. 30)
  • 2.2.7 Security (p. 31)
  • 2.2.8 Cipher and Watermark Keys (p. 33)
  • 2.2.9 Modification and Multiple Watermarks (p. 35)
  • 2.2.10 Cost (p. 36)
  • 2.3 Evaluating Watermarking Systems (p. 36)
  • 2.3.1 The Notion of "Best" (p. 36)
  • 2.3.2 Benchmarking (p. 37)
  • 2.3.3 Scope of Testing (p. 38)
  • 2.4 Summary (p. 39)
  • 3 Models of Watermarking (p. 41)
  • 3.1 Notation (p. 42)
  • 3.2 Communications (p. 43)
  • 3.2.1 Components of Communications Systems (p. 43)
  • 3.2.2 Classes of Transmission Channels (p. 44)
  • 3.2.3 Secure Transmission (p. 45)
  • 3.3 Communication-Based Models of Watermarking (p. 47)
  • 3.3.1 Basic Model (p. 47)
  • 3.3.2 Watermarking as Communication with Side Information at the Transmitter (p. 55)
  • 3.3.3 Watermarking as Multiplexed Communications (p. 58)
  • 3.4 Geometric Models of Watermarking (p. 60)
  • 3.4.1 Distributions and Regions in Media Space (p. 61)
  • 3.4.2 Marking Spaces (p. 67)
  • 3.5 Modeling Watermark Detection by Correlation (p. 75)
  • 3.5.1 Linear Correlation (p. 76)
  • 3.5.2 Normalized Correlation (p. 77)
  • 3.5.3 Correlation Coefficient (p. 80)
  • 3.6 Summary (p. 82)
  • 4 Basic Message Coding (p. 85)
  • 4.1 Mapping Messages into Message Vectors (p. 86)
  • 4.1.1 Direct Message Coding (p. 86)
  • 4.1.2 Multi-symbol Message Coding (p. 90)
  • 4.2 Error Correction Coding (p. 97)
  • 4.2.1 The Problem with Simple Multi-symbol Messages (p. 97)
  • 4.2.2 The Idea of Error Correction Codes (p. 98)
  • 4.2.3 Example: Trellis Codes and Viterbi Decoding (p. 100)
  • 4.3 Detecting Multi-symbol Watermarks (p. 104)
  • 4.3.1 Detection by Looking for Valid Messages (p. 105)
  • 4.3.2 Detection by Detecting Individual Symbols (p. 106)
  • 4.3.3 Detection by Comparing against Quantized Vectors (p. 108)
  • 4.4 Summary (p. 114)
  • 5 Watermarking with Side Information (p. 117)
  • 5.1 Informed Embedding (p. 119)
  • 5.1.1 Embedding as an Optimization Problem (p. 120)
  • 5.1.2 Optimizing with Respect to a Detection Statistic (p. 121)
  • 5.1.3 Optimizing with Respect to an Estimate of Robustness (p. 127)
  • 5.2 Informed Coding (p. 132)
  • 5.2.1 Writing on Dirty Paper (p. 133)
  • 5.2.2 A Dirty-Paper Code for a Simple Channel (p. 135)
  • 5.2.3 Dirty-Paper Codes for More Complex Channels (p. 138)
  • 5.3 Structured Dirty-Paper Codes (p. 144)
  • 5.3.1 Lattice Codes (p. 145)
  • 5.3.2 Syndrome Codes (p. 151)
  • 5.3.3 Least-Significant-Bit Watermarking (p. 153)
  • 5.4 Summary (p. 154)
  • 6 Analyzing Errors (p. 157)
  • 6.1 Message Errors (p. 158)
  • 6.2 False Positive Errors (p. 162)
  • 6.2.1 Random-Watermark False Positive (p. 164)
  • 6.2.2 Random-Work False Positive (p. 166)
  • 6.3 False Negative Errors (p. 170)
  • 6.4 ROC Curves (p. 173)
  • 6.4.1 Hypothetical ROC (p. 173)
  • 6.4.2 Histogram of a Real System (p. 175)
  • 6.4.3 Interpolation along One or Both of the Axes (p. 176)
  • 6.5 The Effect of Whitening on Error Rates (p. 177)
  • 6.6 Analysis of Normalized Correlation (p. 184)
  • 6.6.1 False Positive Analysis (p. 185)
  • 6.6.2 False Negative Analysis (p. 195)
  • 6.7 Summary (p. 198)
  • 7 Using Perceptual Models (p. 201)
  • 7.1 Evaluating Perceptual Impact of Watermarks (p. 202)
  • 7.1.1 Fidelity and Quality (p. 202)
  • 7.1.2 Human Evaluation Measurement Techniques (p. 203)
  • 7.1.3 Automated Evaluation (p. 206)
  • 7.2 General Form of a Perceptual Model (p. 209)
  • 7.2.1 Sensitivity (p. 209)
  • 7.2.2 Masking (p. 213)
  • 7.2.3 Pooling (p. 213)
  • 7.3 Two Examples of Perceptual Models (p. 215)
  • 7.3.1 Watson's DCT-Based Visual Model (p. 215)
  • 7.3.2 A Perceptual Model for Audio (p. 218)
  • 7.4 Perceptually Adaptive Watermarking (p. 222)
  • 7.4.1 Perceptual Shaping (p. 225)
  • 7.4.2 Optimal Use of Perceptual Models (p. 232)
  • 7.5 Summary (p. 239)
  • 8 Robust Watermarking (p. 241)
  • 8.1 Approaches (p. 242)
  • 8.1.1 Redundant Embedding (p. 243)
  • 8.1.2 Spread Spectrum Coding (p. 244)
  • 8.1.3 Embedding in Perceptually Significant Coefficients (p. 245)
  • 8.1.4 Embedding in Coefficients of Known Robustness (p. 246)
  • 8.1.5 Inverting Distortions in the Detector (p. 247)
  • 8.1.6 Pre-inverting Distortions in the Embedder (p. 248)
  • 8.2 Robustness to Valumetric Distortions (p. 252)
  • 8.2.1 Additive Noise (p. 252)
  • 8.2.2 Amplitude Changes (p. 256)
  • 8.2.3 Linear Filtering (p. 258)
  • 8.2.4 Lossy Compression (p. 263)
  • 8.2.5 Quantization (p. 263)
  • 8.2.6 Analytic Model of Quantization Noise on Linear Correlation (p. 267)
  • 8.3 Robustness to Temporal and Geometric Distortions (p. 269)
  • 8.3.1 Temporal and Geometric Distortions (p. 270)
  • 8.3.2 Exhaustive Search (p. 271)
  • 8.3.3 Synchronization/Registration in Blind Detectors (p. 272)
  • 8.3.4 Autocorrelation (p. 273)
  • 8.3.5 Invariant Watermarks (p. 274)
  • 8.3.6 Implicit Synchronization (p. 275)
  • 8.4 Summary (p. 276)
  • 9 Watermark Security (p. 279)
  • 9.1 Security Requirements (p. 279)
  • 9.1.1 Restricting Watermark Operations (p. 280)
  • 9.1.2 Public and Private Watermarking (p. 282)
  • 9.1.3 Categories of Attack (p. 284)
  • 9.1.4 Assumptions about the Adversary (p. 289)
  • 9.2 Watermark Security and Cryptography (p. 292)
  • 9.2.1 The Analogy between Watermarking and Cryptography (p. 292)
  • 9.2.2 Preventing Unauthorized Detection (p. 293)
  • 9.2.3 Preventing Unauthorized Embedding (p. 295)
  • 9.2.4 Preventing Unauthorized Removal (p. 299)
  • 9.3 Some Significant Known Attacks (p. 302)
  • 9.3.1 Scrambling Attacks (p. 302)
  • 9.3.2 Pathological Distortions (p. 303)
  • 9.3.3 Copy Attacks (p. 304)
  • 9.3.4 Ambiguity Attacks (p. 305)
  • 9.3.5 Sensitivity Analysis Attacks (p. 311)
  • 9.3.6 Gradient Descent Attacks (p. 315)
  • 9.4 Summary (p. 316)
  • 10 Content Authentication (p. 319)
  • 10.1 Exact Authentication (p. 321)
  • 10.1.1 Fragile Watermarks (p. 321)
  • 10.1.2 Embedded Signatures (p. 322)
  • 10.1.3 Erasable Watermarks (p. 323)
  • 10.2 Selective Authentication (p. 330)
  • 10.2.1 Legitimate versus Illegitimate Distortions (p. 331)
  • 10.2.2 Semi-fragile Watermarks (p. 334)
  • 10.2.3 Embedded, Semi-fragile Signatures (p. 339)
  • 10.2.4 Tell-tale Watermarks (p. 344)
  • 10.3 Localization (p. 345)
  • 10.3.1 Block-wise Content Authentication (p. 345)
  • 10.3.2 Sample-wise Content Authentication (p. 347)
  • 10.3.3 Security Risks with Localization (p. 349)
  • 10.4 Restoration (p. 353)
  • 10.4.1 Embedded Redundancy (p. 354)
  • 10.4.2 Self-embedding (p. 355)
  • 10.4.3 Blind Restoration (p. 355)
  • 10.5 Summary (p. 356)
  • Appendix A Background Concepts (p. 359)
  • A.1 Information Theory (p. 359)
  • A.1.1 Entropy (p. 359)
  • A.1.2 Mutual Information (p. 360)
  • A.1.3 Communication Rates (p. 362)
  • A.1.4 Channel Capacity (p. 363)
  • A.2 Cryptography (p. 365)
  • A.2.1 Symmetric-Key Cryptography (p. 366)
  • A.2.2 Asymmetric-Key Cryptography (p. 367)
  • A.2.3 One-Way Hash Functions (p. 369)
  • A.2.4 Cryptographic Signatures (p. 370)
  • Appendix B Selected Theoretical Results (p. 373)
  • B.1 Capacity of Channels with Side Information at the Transmitter (Gel'fand and Pinsker) (p. 373)
  • B.1.1 General Form of Channels with Side Information (p. 373)
  • B.1.2 Capacity of Channels with Side Information (p. 374)
  • B.2 Capacity of the AWGN Dirty-Paper Channel (Costa) (p. 376)
  • B.3 Information-Theoretic Analysis of Secure Watermarking (Moulin and O'Sullivan) (p. 377)
  • B.3.1 Watermarking as a Game (p. 378)
  • B.3.2 General Capacity of Watermarking (p. 380)
  • B.3.3 Capacity with MSE Fidelity Constraint (p. 381)
  • B.4 Error Probabilities Using Normalized Correlation Detectors (Miller and Bloom) (p. 384)
  • B.5 Effect of Quantization Noise on Watermarks (Eggers and Girod) (p. 388)
  • B.5.1 Background (p. 390)
  • B.5.2 Basic Approach (p. 390)
  • B.5.3 Finding the Probability Density Function (p. 390)
  • B.5.4 Finding the Moment-Generating Function (p. 391)
  • B.5.5 Determining the Expected Correlation for a Gaussian Watermark and Laplacian Content (p. 393)
  • Appendix C Source Code (p. 395)
  • C.1 E_BLIND/D_LC (p. 396)
  • C.2 E_FIXED_LC/D_LC (p. 400)
  • C.3 E_BLK_BLIND/D_BLK_CC (p. 402)
  • C.4 E_SIMPLE_8/D_SIMPLE_8 (p. 410)
  • C.5 E_TRELLIS_8/D_TRELLIS_8 (p. 415)
  • C.6 E_BLK_8/D_BLK_8 (p. 421)
  • C.7 E_BLK_FIXED_CC/D_BLK_CC (p. 423)
  • C.8 E_BLK_FIXED_R/D_BLK_CC (p. 427)
  • C.9 E_DIRTY_PAPER/D_DIRTY_PAPER (p. 430)
  • C.10 E_LATTICE/D_LATTICE (p. 434)
  • C.11 E_BLIND/D_WHITE (p. 443)
  • C.12 E_BLK_BLIND/D_WHITE_BLK_CC (p. 446)
  • C.13 E_PERC_GSCALE/D_LC (p. 448)
  • C.14 E_PERC_SHAPE/D_LC (p. 455)
  • C.15 E_PERC_OPT/D_LC (p. 458)
  • C.16 E_MOD/D_LC (p. 460)
  • C.17 E_DCTQ/D_DCTQ (p. 461)
  • C.18 E_SFSIG/D_SFSIG (p. 474)
  • C.19 E_PXL/D_PXL (p. 479)
  • Appendix D Notation and Common Variables (p. 483)
  • D.1 Variable Naming Conventions (p. 483)
  • D.2 Operators (p. 484)
  • D.3 Common Variable Names (p. 485)
  • D.4 Common Functions (p. 486)
  • Glossary (p. 487)
  • References (p. 501)
  • Index (p. 521)
  • About the Authors (p. 541)