A new approach for improving transparency of audio watermarking.

Chen Benrong.Thesis (M.Phil.)--Chinese University of Hong Kong, 2003.Includes bibliographical references (leaves 125-130).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- What' s Watermarking --- p.1Chapter 1.2 --- "Information Hiding, Steganography, and Watermarking" --- p.3Chapter 1.3 --- History of Watermarking --- p.5Chapter 1.4 --- Importance of Digital Watermarking --- p.8Chapter 1.5 --- Objectives of the Thesis --- p.9Chapter 1.6 --- Thesis Outline --- p.10Chapter 2 --- Applications and Properties of Audio Watermarking --- p.12Chapter 2.1 --- Applications --- p.13Chapter 2.1.1 --- Ownership Identification and Proof --- p.13Chapter 2.1.2 --- Broadcast Monitoring --- p.16Chapter 2.1.3 --- Other Applications --- p.18Chapter 2.2 --- Properties --- p.19Chapter 2.2.1 --- Transparency --- p.20Chapter 2.2.2 --- Robustness --- p.20Chapter 2.2.3 --- Other Properties --- p.21Chapter 3 --- Possible Methods for Audio Watermarking --- p.24Chapter 3.1 --- Overview of Digital Audio Watermarking System --- p.25Chapter 3.2 --- Review of Current Methods --- p.27Chapter 3.2.1 --- Low Bit Coding --- p.27Chapter 3.2.2 --- Phase Coding --- p.28Chapter 3.2.3 --- Echo Coding --- p.29Chapter 3.2.4 --- Spread Spectrum Watermarking --- p.30Chapter 3.3 --- Other Related Approaches --- p.31Chapter 3.4 --- Outline of Proposed New Method --- p.33Chapter 4 --- Audio Watermarking System Based on Spread Spectrum --- p.36Chapter 4.1 --- Introduction --- p.36Chapter 4.2 --- Embedding and Detecting Information Bit --- p.39Chapter 4.2.1 --- General Embedding Process --- p.39Chapter 4.2.2 --- General Detection Process --- p.43Chapter 4.2.3 --- Pseudorandom Bit Sequences (PRBS) --- p.45Chapter 4.3 --- An Optimal Embedding Process --- p.48Chapter 4.3.1 --- Objective Metrics for Embedding Process --- p.48Chapter 4.3.2 --- Content Adaptive Embedding --- p.52Chapter 4.3.3 --- Determination of Frame Length L --- p.57Chapter 4.4 --- Requirement For Transparency Improvement --- p.58Chapter 5 --- Sample and Frame Selection For Transparency Improvement --- p.60Chapter 5.1 --- Introduction --- p.60Chapter 5.2 --- Sample Selection --- p.61Chapter 5.2.1 --- General Sample Selection --- p.62Chapter 5.2.2 --- Objective Evaluation Metrics --- p.65Chapter 5.2.3 --- Sample Selection For Transparency Improvement --- p.66Chapter 5.2.4 --- Theoretical Analysis of Sample Selection --- p.87Chapter 5.3 --- Frame Sclcction --- p.90Chapter 5.3.1 --- General Frame Selection --- p.91Chapter 5.3.2 --- Frame Selection For Transparency Improvement --- p.94Chapter 5.4 --- Watermark Information Retrieve --- p.103Chapter 6 --- Psychoacoustic Model For Robustness Verification --- p.105Chapter 6.1 --- Introduction of Human Auditory System --- p.106Chapter 6.1.1 --- Absolute Hearing Threshold --- p.106Chapter 6.1.2 --- Critical Bands --- p.108Chapter 6.1.3 --- Masking Effect --- p.111Chapter 6.2 --- Psychoacoustic Model of Human Auditory System --- p.112Chapter 6.3 --- Robustness Verification by Psychoacoustic Model Analysis --- p.117Chapter 7 --- Conclusions and Suggestions For Future Research --- p.121Chapter 7.1 --- Conclusions --- p.121Chapter 7.2 --- Suggestions For Future Research --- p.123Bibliography --- p.12

High capacity data embedding schemes for digital media

High capacity image data hiding methods and robust high capacity digital audio watermarking algorithms are studied in this thesis. The main results of this work are the development of novel algorithms with state-of-the-art performance, high capacity and transparency for image data hiding and robustness, high capacity and low distortion for audio watermarking.En esta tesis se estudian y proponen diversos métodos de data hiding de imágenes y watermarking de audio de alta capacidad. Los principales resultados de este trabajo consisten en la publicación de varios algoritmos novedosos con rendimiento a la altura de los mejores métodos del estado del arte, alta capacidad y transparencia, en el caso de data hiding de imágenes, y robustez, alta capacidad y baja distorsión para el watermarking de audio.En aquesta tesi s'estudien i es proposen diversos mètodes de data hiding d'imatges i watermarking d'àudio d'alta capacitat. Els resultats principals d'aquest treball consisteixen en la publicació de diversos algorismes nous amb rendiment a l'alçada dels millors mètodes de l'estat de l'art, alta capacitat i transparència, en el cas de data hiding d'imatges, i robustesa, alta capacitat i baixa distorsió per al watermarking d'àudio.Societat de la informació i el coneixemen

New Digital Audio Watermarking Algorithms for Copyright Protection

This thesis investigates the development of digital audio watermarking in addressing issues such as copyright protection. Over the past two decades, many digital watermarking algorithms have been developed, each with its own advantages and disadvantages. The main aim of this thesis was to develop a new watermarking algorithm within an existing Fast Fourier Transform framework. This resulted in the development of a Complex Spectrum Phase Evolution based watermarking algorithm. In this new implementation, the embedding positions were generated dynamically thereby rendering it more difficult for an attacker to remove, and watermark information was embedded by manipulation of the spectral components in the time domain thereby reducing any audible distortion. Further improvements were attained when the embedding criteria was based on bin location comparison instead of magnitude, thereby rendering it more robust against those attacks that interfere with the spectral magnitudes. However, it was discovered that this new audio watermarking algorithm has some disadvantages such as a relatively low capacity and a non-consistent robustness for different audio files. Therefore, a further aim of this thesis was to improve the algorithm from a different perspective. Improvements were investigated using an Singular Value Decomposition framework wherein a novel observation was discovered. Furthermore, a psychoacoustic model was incorporated to suppress any audible distortion. This resulted in a watermarking algorithm which achieved a higher capacity and a more consistent robustness. The overall result was that two new digital audio watermarking algorithms were developed which were complementary in their performance thereby opening more opportunities for further research

Digital Watermarking for Verification of Perception-based Integrity of Audio Data

In certain application fields digital audio recordings contain sensitive content. Examples are historical archival material in public archives that preserve our cultural heritage, or digital evidence in the context of law enforcement and civil proceedings. Because of the powerful capabilities of modern editing tools for multimedia such material is vulnerable to doctoring of the content and forgery of its origin with malicious intent. Also inadvertent data modification and mistaken origin can be caused by human error. Hence, the credibility and provenience in terms of an unadulterated and genuine state of such audio content and the confidence about its origin are critical factors. To address this issue, this PhD thesis proposes a mechanism for verifying the integrity and authenticity of digital sound recordings. It is designed and implemented to be insensitive to common post-processing operations of the audio data that influence the subjective acoustic perception only marginally (if at all). Examples of such operations include lossy compression that maintains a high sound quality of the audio media, or lossless format conversions. It is the objective to avoid de facto false alarms that would be expectedly observable in standard crypto-based authentication protocols in the presence of these legitimate post-processing. For achieving this, a feasible combination of the techniques of digital watermarking and audio-specific hashing is investigated. At first, a suitable secret-key dependent audio hashing algorithm is developed. It incorporates and enhances so-called audio fingerprinting technology from the state of the art in contentbased audio identification. The presented algorithm (denoted as ”rMAC” message authentication code) allows ”perception-based” verification of integrity. This means classifying integrity breaches as such not before they become audible. As another objective, this rMAC is embedded and stored silently inside the audio media by means of audio watermarking technology. This approach allows maintaining the authentication code across the above-mentioned admissible post-processing operations and making it available for integrity verification at a later date. For this, an existent secret-key ependent audio watermarking algorithm is used and enhanced in this thesis work. To some extent, the dependency of the rMAC and of the watermarking processing from a secret key also allows authenticating the origin of a protected audio. To elaborate on this security aspect, this work also estimates the brute-force efforts of an adversary attacking this combined rMAC-watermarking approach. The experimental results show that the proposed method provides a good distinction and classification performance of authentic versus doctored audio content. It also allows the temporal localization of audible data modification within a protected audio file. The experimental evaluation finally provides recommendations about technical configuration settings of the combined watermarking-hashing approach. Beyond the main topic of perception-based data integrity and data authenticity for audio, this PhD work provides new general findings in the fields of audio fingerprinting and digital watermarking. The main contributions of this PhD were published and presented mainly at conferences about multimedia security. These publications were cited by a number of other authors and hence had some impact on their works

Digital audio watermarking for broadcast monitoring and content identification

Copyright legislation was prompted exactly 300 years ago by a desire to protect authors against exploitation of their work by others. With regard to modern content owners, Digital Rights Management (DRM) issues have become very important since the advent of the Internet. Piracy, or illegal copying, costs content owners billions of dollars every year. DRM is just one tool that can assist content owners in exercising their rights. Two categories of DRM technologies have evolved in digital signal processing recently, namely digital fingerprinting and digital watermarking. One area of Copyright that is consistently overlooked in DRM developments is 'Public Performance'. The research described in this thesis analysed the administration of public performance rights within the music industry in general, with specific focus on the collective rights and broadcasting sectors in Ireland. Limitations in the administration of artists' rights were identified. The impact of these limitations on the careers of developing artists was evaluated. A digital audio watermarking scheme is proposed that would meet the requirements of both the broadcast and collective rights sectors. The goal of the scheme is to embed a standard identifier within an audio signal via modification of its spectral properties in such a way that it would be robust and perceptually transparent. Modification of the audio signal spectrum was attempted in a variety of ways. A method based on a super-resolution frequency identification technique was found to be most effective. The watermarking scheme was evaluated for robustness and found to be extremely effective in recovering embedded watermarks in music signals using a semi-blind decoding process. The final digital audio watermarking algorithm proposed facilitates the development of other applications in the domain of broadcast monitoring for the purposes of equitable royalty distribution along with additional applications and extension to other domains

Steganography and steganalysis: data hiding in Vorbis audio streams

The goal of the current work is to introduce ourselves in the world of steganography and steganalysis, centering our efforts in acoustic signals, a branch of steganography and steganalysis which has received much less attention than steganography and steganalysis for images. With this purpose in mind, it’s essential to get first a basic level of understanding of signal theory and the properties of the Human Auditory System, and we will dedicate ourselves to that aim during the first part of this work. Once established those basis, in the second part, we will obtain a precise image of the state of the art in steganographic and steganalytic sciences, from which we will be able to establish or deduce some good practices guides. With both previous subjects in mind, we will be able to create, design and implement a stego-system over Vorbis audio codec and, finally, as conclusion, analyze it using the principles studied during the first and second parts

Watermarking via zero assigned filter banks

Cataloged from PDF version of article.A watermarking scheme for audio and image files is proposed based on wavelet decomposition via zero assigned filter banks. Zero assigned filter banks are perfect reconstruction, conjugate quadrature mirror filter banks with assigned zeros in low pass and high pass filters. They correspond to a generalization of filter banks that yield Daubechies wavelets. The watermarking method consists of partitioning a given time or space signal into frames of fixed size, wavelet decomposing each frame via one of two filter banks with different assigned zeros, compressing a suitable set of coefficients in the wavelet decomposition, and reconstructing the signal from the compressed coefficients of frames. In effect, this method encodes the bit ‘0’ or ‘1’ in each frame depending on the filter bank that is used in the wavelet decomposition of that frame. The method is shown to be perceptually transparent and robust against channel noise as well as against various attacks to remove the watermark such as denoising, estimation, and compression. Moreover, the original signal is not needed for detection and the bandwidth requirement of the multiple authentication keys that are used in this method is very modest.Yücel, ZeynepM.S

Wavelet-Based Audio Embedding & Audio/Video Compression

With the decline in military spending, the United States relies heavily on state side support. Communications has never been more important. High-quality audio and video capabilities are a must. Watermarking, traditionally used for copyright protection, is used in a new and exciting way. An efficient wavelet-based watermarking technique embeds audio information into a video signal. Several highly effective compression techniques are applied to compress the resulting audio/video signal in an embedded fashion. This wavelet-based compression algorithm incorporates bit plane coding, first difference coding, and Huffman coding. To demonstrate the potential of this audio embedding audio/video compression system, an audio signal is embedded into a video signal and the combined signal is compressed. Results show that overall compression rates of 15:1 can be achieved. The video signal is reconstructed with a median PSNR of nearly 33dB. Finally, the audio signal is extracted with out error

Audio Coding Based on Integer Transforms

Die Audiocodierung hat sich in den letzten Jahren zu einem sehr populären Forschungs- und Anwendungsgebiet entwickelt. Insbesondere gehörangepasste Verfahren zur Audiocodierung, wie etwa MPEG-1 Layer-3 (MP3) oder MPEG-2 Advanced Audio Coding (AAC), werden häufig zur effizienten Speicherung und Übertragung von Audiosignalen verwendet. Für professionelle Anwendungen, wie etwa die Archivierung und Übertragung im Studiobereich, ist hingegen eher eine verlustlose Audiocodierung angebracht. Die bisherigen Ansätze für gehörangepasste und verlustlose Audiocodierung sind technisch völlig verschieden. Moderne gehörangepasste Audiocoder basieren meist auf Filterbänken, wie etwa der überlappenden orthogonalen Transformation "Modifizierte Diskrete Cosinus-Transformation" (MDCT). Verlustlose Audiocoder hingegen verwenden meist prädiktive Codierung zur Redundanzreduktion. Nur wenige Ansätze zur transformationsbasierten verlustlosen Audiocodierung wurden bisher versucht. Diese Arbeit präsentiert einen neuen Ansatz hierzu, der das Lifting-Schema auf die in der gehörangepassten Audiocodierung verwendeten überlappenden Transformationen anwendet. Dies ermöglicht eine invertierbare Integer-Approximation der ursprünglichen Transformation, z.B. die IntMDCT als Integer-Approximation der MDCT. Die selbe Technik kann auch für Filterbänke mit niedriger Systemverzögerung angewandt werden. Weiterhin ermöglichen ein neuer, mehrdimensionaler Lifting-Ansatz und eine Technik zur Spektralformung von Quantisierungsfehlern eine Verbesserung der Approximation der ursprünglichen Transformation. Basierend auf diesen neuen Integer-Transformationen werden in dieser Arbeit neue Verfahren zur Audiocodierung vorgestellt. Die Verfahren umfassen verlustlose Audiocodierung, eine skalierbare verlustlose Erweiterung eines gehörangepassten Audiocoders und einen integrierten Ansatz zur fein skalierbaren gehörangepassten und verlustlosen Audiocodierung. Schließlich wird mit Hilfe der Integer-Transformationen ein neuer Ansatz zur unhörbaren Einbettung von Daten mit hohen Datenraten in unkomprimierte Audiosignale vorgestellt.In recent years audio coding has become a very popular field for research and applications. Especially perceptual audio coding schemes, such as MPEG-1 Layer-3 (MP3) and MPEG-2 Advanced Audio Coding (AAC), are widely used for efficient storage and transmission of music signals. Nevertheless, for professional applications, such as archiving and transmission in studio environments, lossless audio coding schemes are considered more appropriate. Traditionally, the technical approaches used in perceptual and lossless audio coding have been separate worlds. In perceptual audio coding, the use of filter banks, such as the lapped orthogonal transform "Modified Discrete Cosine Transform" (MDCT), has been the approach of choice being used by many state of the art coding schemes. On the other hand, lossless audio coding schemes mostly employ predictive coding of waveforms to remove redundancy. Only few attempts have been made so far to use transform coding for the purpose of lossless audio coding. This work presents a new approach of applying the lifting scheme to lapped transforms used in perceptual audio coding. This allows for an invertible integer-to-integer approximation of the original transform, e.g. the IntMDCT as an integer approximation of the MDCT. The same technique can also be applied to low-delay filter banks. A generalized, multi-dimensional lifting approach and a noise-shaping technique are introduced, allowing to further optimize the accuracy of the approximation to the original transform. Based on these new integer transforms, this work presents new audio coding schemes and applications. The audio coding applications cover lossless audio coding, scalable lossless enhancement of a perceptual audio coder and fine-grain scalable perceptual and lossless audio coding. Finally an approach to data hiding with high data rates in uncompressed audio signals based on integer transforms is described