Watermarking for multimedia security using complex wavelets

This paper investigates the application of complex wavelet transforms to the field of digital data hiding. Complex wavelets offer improved directional selectivity and shift invariance over their discretely sampled counterparts allowing for better adaptation of watermark distortions to the host media. Two methods of deriving visual models for the watermarking system are adapted to the complex wavelet transforms and their performances are compared. To produce improved capacity a spread transform embedding algorithm is devised, this combines the robustness of spread spectrum methods with the high capacity of quantization based methods. Using established information theoretic methods, limits of watermark capacity are derived that demonstrate the superiority of complex wavelets over discretely sampled wavelets. Finally results for the algorithm against commonly used attacks demonstrate its robustness and the improved performance offered by complex wavelet transforms

Quantization Watermarking for Joint Compression and Data Hiding Schemes

International audienceEnrichment and protection of JPEG2000 images is an important issue. Data hiding techniques are a good solution to solve these problems. In this context, we can consider the joint approach to introduce data hiding technique into JPEG2000 coding pipeline. Data hiding consists of imperceptibly altering multimedia content, to convey some information. This process is done in such a way that the hidden data is not perceptible to an observer. Digital watermarking is one type of data hiding. In addition to the imperceptibility and payload constraints, the watermark should be robust against a variety of manipulations or attacks. We focus on trellis coded quantization (TCQ) data hiding techniques and propose two JPEG2000 compression and data hiding schemes. The properties of TCQ quantization, defined in JPEG2000 part 2, are used to perform quantization and information embedding during the same time. The first scheme is designed for content description and management applications with the objective of achieving high payloads. The compression rate/imperceptibility/payload trade off is our main concern. The second joint scheme has been developed for robust watermarking and can have consequently many applications. We achieve the better imperceptibility/robustness trade off in the context of JPEG2000 compression. We provide some experimental results on the implementation of these two schemes

Audio watermarking using transformation techniques

Watermarking is a technique, which is used in protecting digital information like images, videos and audio as it provides copyrights and ownership. Audio watermarking is more challenging than image watermarking due to the dynamic supremacy of hearing capacity over the visual field. This thesis attempts to solve the quantization based audio watermarking technique based on both the Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT). The underlying system involves the statistical characteristics of the signal. This study considers different wavelet filters and quantization techniques. A comparison is performed on diverge algorithms and audio signals to help examine the performance of the proposed method. The embedded watermark is a binary image and different encryption techniques such as Arnold Transform and Linear Feedback Shift Register (LFSR) are considered. The watermark is distributed uniformly in the areas of low frequencies i.e., high energy, which increases the robustness of the watermark. Further, spreading of watermark throughout the audio signal makes the technique robust against desynchronized attacks. Experimental results show that the signals generated by the proposed algorithm are inaudible and robust against signal processing techniques such as quantization, compression and resampling. We use Matlab (version 2009b) to implement the algorithms discussed in this thesis. Audio transformation techniques for compression in Linux (Ubuntu 9.10) are applied on the signal to simulate the attacks such as re-sampling, re-quantization, and mp3 compression; whereas, Matlab program for de-synchronized attacks like jittering and cropping. We envision that the proposed algorithm may work as a tool for securing intellectual properties of the musicians and audio distribution companies because of its high robustness and imperceptibility

On the data hiding theory and multimedia content security applications

This dissertation is a comprehensive study of digital steganography for multimedia content protection. With the increasing development of Internet technology, protection and enforcement of multimedia property rights has become a great concern to multimedia authors and distributors. Watermarking technologies provide a possible solution for this problem. The dissertation first briefly introduces the current watermarking schemes, including their applications in video,, image and audio. Most available embedding schemes are based on direct Spread Sequence (SS) modulation. A small value pseudo random signature sequence is embedded into the host signal and the information is extracted via correlation. The correlation detection problem is discussed at the beginning. It is concluded that the correlator is not optimum in oblivious detection. The Maximum Likelihood detector is derived and some feasible suboptimal detectors are also analyzed. Through the calculation of extraction Bit Error Rate (BER), it is revealed that the SS scheme is not very efficient due to its poor host noise suppression. The watermark domain selection problem is addressed subsequently. Some implications on hiding capacity and reliability are also studied. The last topic in SS modulation scheme is the sequence selection. The relationship between sequence bandwidth and synchronization requirement is detailed in the work. It is demonstrated that the white sequence commonly used in watermarking may not really boost watermark security. To address the host noise suppression problem, the hidden communication is modeled as a general hypothesis testing problem and a set partitioning scheme is proposed. Simulation studies and mathematical analysis confirm that it outperforms the SS schemes in host noise suppression. The proposed scheme demonstrates improvement over the existing embedding schemes. Data hiding in audio signals are explored next. The audio data hiding is believed a more challenging task due to the human sensitivity to audio artifacts and advanced feature of current compression techniques. The human psychoacoustic model and human music understanding are also covered in the work. Then as a typical audio perceptual compression scheme, the popular MP3 compression is visited in some length. Several schemes, amplitude modulation, phase modulation and noise substitution are presented together with some experimental results. As a case study, a music bitstream encryption scheme is proposed. In all these applications, human psychoacoustic model plays a very important role. A more advanced audio analysis model is introduced to reveal implications on music understanding. In the last part, conclusions and future research are presented

A constructive and unifying framework for zero-bit watermarking

In the watermark detection scenario, also known as zero-bit watermarking, a watermark, carrying no hidden message, is inserted in content. The watermark detector checks for the presence of this particular weak signal in content. The article looks at this problem from a classical detection theory point of view, but with side information enabled at the embedding side. This means that the watermark signal is a function of the host content. Our study is twofold. The first step is to design the best embedding function for a given detection function, and the best detection function for a given embedding function. This yields two conditions, which are mixed into one `fundamental' partial differential equation. It appears that many famous watermarking schemes are indeed solution to this `fundamental' equation. This study thus gives birth to a constructive framework unifying solutions, so far perceived as very different.Comment: submitted to IEEE Trans. on Information Forensics and Securit

Modeling and frequency tracking of marine mammal whistle calls

Submitted in partial fulfillment of the requirements for the degree of Master of Science at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 2009Marine mammal whistle calls present an attractive medium for covert underwater communications. High quality models of the whistle calls are needed in order to synthesize natural-sounding whistles with embedded information. Since the whistle calls are composed of frequency modulated harmonic tones, they are best modeled as a weighted superposition of harmonically related sinusoids. Previous research with bottlenose dolphin whistle calls has produced synthetic whistles that sound too “clean” for use in a covert communications system. Due to the sensitivity of the human auditory system, watermarking schemes that slightly modify the fundamental frequency contour have good potential for producing natural-sounding whistles embedded with retrievable watermarks. Structured total least squares is used with linear prediction analysis to track the time-varying fundamental frequency and harmonic amplitude contours throughout a whistle call. Simulation and experimental results demonstrate the capability to accurately model bottlenose dolphin whistle calls and retrieve embedded information from watermarked synthetic whistle calls. Different fundamental frequency watermarking schemes are proposed based on their ability to produce natural sounding synthetic whistles and yield suitable watermark detection and retrieval