Histogram-Based Audio Watermarking Against Time-Scale Modification and Cropping Attacks

In audio watermarking area, the robustness against desynchronization attacks, such as TSM (Time-Scale Modification) and random cropping operations, is still one of the most challenging issues. In this paper, we present a multibit robust audio watermarking solution for such a problem by using the insensitivity of the audio histogram shape and the modified mean to TSM and cropping operations. We address the insensitivity property in both mathematical analysis and experimental testing by representing the histogram shape as the relative relations in the number of samples among groups of three neighboring bins. By reassigning the number of samples in groups of three neighboring bins, the watermark sequence is successfully embedded. In the embedding process, the histogram is extracted from a selected amplitude range by referring to the mean in such a way that the watermark will be able to be resistant to amplitude scaling and avoid exhaustive search in the extraction process. The watermarked audio signal is perceptibly similar to the original one. Experimental results demonstrate that the hidden message is very robust to TSM and random cropping attacks, and also has a satisfactory robustness for those common audio signal processing operations.