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Data Hiding Fundamentals and Applications
Content Security in Digital Multimedia
- 1st Edition - August 20, 2004
- Authors: Husrev T. Sencar, Mahalingam Ramkumar, Ali N. Akansu
- Language: English
- Hardback ISBN:9 7 8 - 0 - 1 2 - 0 4 7 1 4 4 - 7
- eBook ISBN:9 7 8 - 0 - 0 8 - 0 4 8 8 6 6 - 0
Multimedia technologies are becoming more sophisticated, enabling the Internet to accommodate a rapidly growing audience with a full range of services and efficient delivery me… Read more
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Request a sales quoteMultimedia technologies are becoming more sophisticated, enabling the Internet to accommodate a rapidly growing audience with a full range of services and efficient delivery methods. Although the Internet now puts communication, education, commerce and socialization at our finger tips, its rapid growth has raised some weighty security concerns with respect to multimedia content. The owners of this content face enormous challenges in safeguarding their intellectual property, while still exploiting the Internet as an important resource for commerce.
Data Hiding Fundamentals and Applications focuses on the theory and state-of-the-art applications of content security and data hiding in digital multimedia. One of the pillars of content security solutions is the imperceptible insertion of information into multimedia data for security purposes; the idea is that this inserted information will allow detection of unauthorized usage.
- Provides a theoretical framework for data hiding, in a signal processing context
- Realistic applications in secure, multimedia delivery
- Compression robust data hiding
- Data hiding for proof of ownership--WATERMARKING
- Data hiding algorithms for image and video watermarking
Engineers, computer scientists, and students doing research in multimedia signal processing, content security, and digital rights management (DRM) systems.
Preface
1. Introduction
1.1 What is Data Hiding?
1.2 Forms of Data Hiding
1.3 Properties of Steganographic Communications
1.4 The Steganographic Channel
2. Frameworks for Data Hiding
2.1 Signal Processing Framework
2.2 Data Hiding from a Communications Perspective
2.3 Relationship Between Communications and Signal Processing Frameworks
2.4 A Review of Data Hiding Methods
3. Communication with Side Information and Data Hiding
3.1 Costa’s Framework
3.2 A Framework Based on Channel Adaptive Encoding and Channel Independent Decoding
3.3 On the Duality of Communications and Data Hiding Frameworks
3.4 Codebook Generation for Data Hiding Methods
4. Type I (Linear) Data Hiding
4.1 Linear Data Hiding in Transform Domain
4.2 Problem Statement
4.3 Capacity of Additive Noise Channels
4.4 Modeling Channel Noise
4.5 Visual Threshold
4.6 Channel Capacity vs. Choice of Transform
4.7 Some Capacity Results and Discussions
4.8 The Ideal Decomposition
4.9 Factors Influencing Choice of Transform
5. Type II and Type III (Nonlinear) Data Hiding Methods
5.1 Type II Embedding and Detection
5.2 Type III Embedding and Detection Methods
5.3 Performance Comparisons
6. Advanced Implementations
6.1 Spread Transforming
6.2 Multiple Codebook Data Hiding
7. Major Design Issues
7.1 DFT-Based Signaling
7.2 Synchronization
7.3 Perceptual Constraints
7.4 Attacks on Data Hiding Systems
8. Data Hiding Applications
8.1 Design of Data Hiding Methods Robust to Lossy Compression
8.2 Type III Hiding for Lossy Compression
8.3 Watermarking for Ownership
Appendix A
Appendix B
Mathematical Proofs
Bibliography
Index:
1. Introduction
1.1 What is Data Hiding?
1.2 Forms of Data Hiding
1.3 Properties of Steganographic Communications
1.4 The Steganographic Channel
2. Frameworks for Data Hiding
2.1 Signal Processing Framework
2.2 Data Hiding from a Communications Perspective
2.3 Relationship Between Communications and Signal Processing Frameworks
2.4 A Review of Data Hiding Methods
3. Communication with Side Information and Data Hiding
3.1 Costa’s Framework
3.2 A Framework Based on Channel Adaptive Encoding and Channel Independent Decoding
3.3 On the Duality of Communications and Data Hiding Frameworks
3.4 Codebook Generation for Data Hiding Methods
4. Type I (Linear) Data Hiding
4.1 Linear Data Hiding in Transform Domain
4.2 Problem Statement
4.3 Capacity of Additive Noise Channels
4.4 Modeling Channel Noise
4.5 Visual Threshold
4.6 Channel Capacity vs. Choice of Transform
4.7 Some Capacity Results and Discussions
4.8 The Ideal Decomposition
4.9 Factors Influencing Choice of Transform
5. Type II and Type III (Nonlinear) Data Hiding Methods
5.1 Type II Embedding and Detection
5.2 Type III Embedding and Detection Methods
5.3 Performance Comparisons
6. Advanced Implementations
6.1 Spread Transforming
6.2 Multiple Codebook Data Hiding
7. Major Design Issues
7.1 DFT-Based Signaling
7.2 Synchronization
7.3 Perceptual Constraints
7.4 Attacks on Data Hiding Systems
8. Data Hiding Applications
8.1 Design of Data Hiding Methods Robust to Lossy Compression
8.2 Type III Hiding for Lossy Compression
8.3 Watermarking for Ownership
Appendix A
Appendix B
Mathematical Proofs
Bibliography
Index:
- No. of pages: 272
- Language: English
- Edition: 1
- Published: August 20, 2004
- Imprint: Academic Press
- Hardback ISBN: 9780120471447
- eBook ISBN: 9780080488660
HS
Husrev T. Sencar
Affiliations and expertise
New Jersey Institute of Technology, Newark, New JerseyMR
Mahalingam Ramkumar
Affiliations and expertise
Polytechnic University, Brooklyn, New YorkAA
Ali N. Akansu
Ali N. Akansu received the BS degree from the Technical University of Istanbul, Turkey, in 1980, the MS and Ph.D degrees from the Polytechnic University, Brooklyn, New York in 1983 and 1987, respectively, all in Electrical Engineering. He has been with the Electrical & Computer Engineering Department of the New Jersey Institute of Technology since 1987. He was an academic visitor at David Sarnoff Research Center, at IBM T.J. Watson Research Center, and at GEC-Marconi Electronic Systems Corp. He was a Visiting Professor at Courant Institute of Mathematical Sciences of the New York University performed research on Quantitative Finance. He serves as a consultant to the industry. His current research and professional interests include theory of signals and transforms, financial engineering & electronic trading, and high performance DSP (FPGA & GPU computing).
Affiliations and expertise
New Jersey Institute of Technology, Newark, NJ, USARead Data Hiding Fundamentals and Applications on ScienceDirect