Audio content authentication based on psycho-acoustic model

The goal of audio content authentication techniques is to separate malicious manipulations from authentic signal processing applications like compression, filtering, etc. The key difference between malicious operations and signal processing operations is that the latter tends to preserve the perceptual content of the underlying audio signal. Hence, in order to separate malicious operations from allowed operations, a content authentication procedure should be based on a model that approximates human perception of audio. In this paper, we propose an audio content authentication technique based on an invariant feature contained in two perceptually similar audio data, i.e. the masking curve. We also evaluate the performance of this technique by embedding a hash based on the masking curve into the audio signal using an existing transparent and robust data hiding technique. At the receiver, the same content-based hash is extracted from the audio and compared with the calculated hash bits. Correlation between calculated hash bits and extracted hash bits degrades gracefully with the perceived quality of received audio. This implies that the threshold for authentication can be adapted to the required level of perceptual quality at the receiver. Experimental results show that this content-based hash is able to differentiate allowed signal processing applications like MP3 compression from certain malicious operations, which modify the perceptual content of the audio.