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Audio tampering detection via microphone classification

: Cuccovillo, Luca; Mann, Sebastian; Tagliasacchi, Marco; Aichroth, Patrick


Institute of Electrical and Electronics Engineers -IEEE-:
IEEE 15th International Workshop on Multimedia Signal Processing, MMSP 2013. Proceedings : Held 30 September - 2 October 2013, Santa Margherita di Pula, Sardinia, Italy
Piscataway, NJ: IEEE, 2013
ISBN: 978-1-4799-0124-1
ISBN: 978-1-4799-0125-8
International Workshop on Multimedia Signal Processing (MMSP) <15, 2013, Pula>
Conference Paper
Fraunhofer IDMT ()
tampering detection; microphone classification; blind channel estimation; MPEG-2 AAC; MP3

In this paper, we present a new approach for audio tampering detection based on microphone classification. The underlying algorithm is based on a blind channel estimation, specifically designed for recordings from mobile devices. It is applied to detect a specific type of tampering, i.e., to detect whether footprints from more than one microphone exist within a given content item. As will be shown, the proposed method achieves an accuracy above 95% for AAC, MP3 and PCM-encoded recordings.