| The rapid development of digital techniques and internet brings urgent challenges upon multimedia copyright protection and authentification. By the popular demand, watermarking technique attracts extensive attention with plenty of research. This dissertation presents efforts in both theory and practice, on robust digital watermarking for perceptual audio coding, which takes on a significant utility value. The research mainly leads to the following innovations:1. Perturbation in correlation detecting is explored that short-term signals' actual distribution can't fit the hypothesis of Gaussian Normal model. So a new self-adaptive spread spectrum audio watermarking is proposed by embedding intensity modification to eliminate the correlation between audio signals and m sequence, with perceptual optimization using embedding frame sift.2. Based on human acoustic features, a new method to divide perceptually critical segments by MFCC and correlation is proposed, which is used in TSM as an improvement and also an effective synchronization attack method to audio watermarking.3. The impact on audio perception of watermarking with little correlation to audio signal is discussed, which leads to a new method of spread-spectrum steganalysis based on distortion measures. The support vector machine (SVM) is used as a classifier ,using various distortion measures sensitive to DSSS stego-method as features, avoiding estimation of the original signal.4. On the foundation of perceptual coding principles, the compression distortions in both time and frequency domain are comprehensively considered. By taking advantage of the robustness of low frequency energy, a watermarking method of quantizing neighbored frame is proposed.
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