Detecting Digital Forgeries Using Bispectral Analysis
Detecting Digital Forgeries Using Bispectral Analysis
Statistical characterisation of MP3 encoders for steganalysis
Proceedings of the 2004 workshop on Multimedia and security
Digital audio forensics: a first practical evaluation on microphone and environment classification
Proceedings of the 9th workshop on Multimedia & security
Detecting digital audio forgeries by checking frame offsets
Proceedings of the 10th ACM workshop on Multimedia and security
Statistical tools for digital forensics
IH'04 Proceedings of the 6th international conference on Information Hiding
Exposing digital audio forgeries in time domain by using singularity analysis with wavelets
Proceedings of the first ACM workshop on Information hiding and multimedia security
Detection and classification of double compressed MP3 audio tracks
Proceedings of the first ACM workshop on Information hiding and multimedia security
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Audio recordings should be authenticated before they are used as evidence. Although audio watermarking and signature are widely applied for authentication, these two techniques require accessing the original audio before it is published. Passive authentication is necessary for digital audio, especially for the most popular audio format: MP3. In this article, we propose a passive approach to detect forgeries of MP3 audio. During the process of MP3 encoding the audio samples are divided into frames, and thus each frame has its own frame offset after encoding. Forgeries lead to the breaking of framing grids. So the frame offset is a good indication for locating forgeries, and it can be retrieved by the identification of the quantization characteristic. In this way, the doctored positions can be automatically located. Experimental results demonstrate that the proposed approach is effective in detecting some common forgeries, such as deletion, insertion, substitution, and splicing. Even when the bit rate is as low as 32 kbps, the detection rate is above 99%.