Robust Watermarking using Hidden Markov Models

Software piracy is the unauthorized copying or distribution of software. It is a growing problem that results in annual losses in the billions of dollars. Prevention is a difficult problem since digital documents are easy to copy and distribute. Watermarking is a possible defense against software piracy. A software watermark consists of information embedded in the software, which allows it to be identified. A watermark can act as a deterrent to unauthorized copying, since it can be used to provide evidence for legal action against those responsible for piracy.In this project, we present a novel software watermarking scheme that is inspired by the success of previous research focused on detecting metamorphic viruses. We use a trained hidden Markov model (HMM) to detect a specific copy of software. We give experimental results that show our scheme is robust. That is, we can identify the original software even after it has been extensively modified, as might occur as part of an attack on the watermarking scheme

High capacity audio watermarking using FFT amplitude interpolation

An audio watermarking technique in the frequency domain which takes advantage of interpolation is proposed. Interpolated FFT samples are used to generate imperceptible marks. The experimental results show that the suggested method has very high capacity (about 3kbps), without significant perceptual distortion (ODG about -0.5) and provides robustness against common audio signal processing such as echo, add noise, filtering, resampling and MPEG compression (MP3). Depending on the specific application, the tuning parameters could be selected adaptively to achieve even more capacity and better transparency

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

A robust audio watermarking scheme based on reduced singular value decomposition and distortion removal

This paper presents a blind audio watermarking algorithm based on the reduced singular value decomposition(RSVD). A new observation on one of the resulting unitary matrices is uncovered. The proposed scheme manipulates coefficients based on this observation in order to embed watermark bits. To preserve audio fidelity a threshold- based distortion control technique is applied and this is further supplemented by distortion suppression utilizing psychoacoustic principles. Test results on real music signals show that this watermarking scheme is in the range of imperceptibility for human hearing, is accurate and also robust against MP3 compression at various bit rates as well as other selected attacks. The data payload is comparatively high compared to existing audio watermarking schemes

Informed Multiple-F0 Estimation Applied to Monaural Audio Source Separation

International audienceThis paper proposes a new informed source separation technique which combines music transcription with source separation. The presented system is based on a coder / decoder configuration where a classic (not informed) multiple-F0 estimation is applied on each separated source signal assumed known at the coder before the mixing process. Thus, the extra information required to recover the reference transcription of each isolated instrument is computed and inaudibly embedded into the mixture using a watermarking technique. At the decoder, where the original source signals are unknown, instruments are separated from the mixture using the informed transcription of each source signal. In this paper, we show that a classic (non-informed) F0 estimator can be used to reduce the amount of bits necessary to transmit the exact transcription of each isolated instrument