Audio Integrity Protection and Falsification Estimation by Embedding Multiple Watermarks

Abstract

The recognition of digital audio data manipulation is a challenge addressed by various fragile and contentfragile watermarking algorithms. But so far none of the approaches provides satisfying results with respect to manipulation detection. Especially distinguishing malicious attacks from allowed post production operations is still an open issue. We introduce a novel watermarkingbased approach for audio data falsification recognition. We embed multiple watermarks with various characteristics into the audio data to be protected. By analyzing the quality of the retrieved watermarks we obtain information about the nature of the manipulation of the audio data. In comparison to known feature-embedding algorithms, this is rather a forensic approach using watermarking as a hint. Our method is verified using several audio data sets.