Prior Publisher

The Association of Digital Forensics, Security and Law (ADFSL)


We show that modulation products from local oscillators in a variety of commercial camcorders are coupled into the recorded audio track, creating narrow band time invariant spectral features. These spectral features, left largely intact by transcoding, compression and other forms of audiovisual post processing, can encode characteristics of specific camcorders used to capture the audio files, including the make and model. Using data sets both downloaded from YouTube and collected under controlled laboratory conditions we demonstrate an average probability of detection (Pd) approaching 0.95 for identification of a specific camcorder in a population of thousands of similar recordings, with a probability of false alarm (Pfa) of about 0.11. We also demonstrate an average Pd of about 0.93 for correct association of make and model of camcorder based on comparison of audio spectral features extracted from random YouTube downloads compared to a reference library of spectral features captured from known makes and models of camcorders, with a Pfa of 0.06. The method described can be used independently or synergistically with image plane-based techniques such as those based upon Photo Response Non-Uniformity.


[1] Kuroki, K., Kurosawa, K., & Saitoh, N. (January 2002). An Approach to Individual Video Camera Identification. Journal of Forensic Sciences, 47(1).

[2] Lukáš, J., Fridrich, J., & Goljan, M. (June 2006). Digital Camera Identification from Sensor Pattern Noise. IEEE Transactions on Information Forensics and Security, 1(2), 205–214.

[3] Chen, M., Lukáš, J., Fridrich, J., response NonUniformity. Proc. of SPIE Electronic Imaging, Photonics West

[4] Wand, W., & Farid, H. (2009). Exposing Digital Forgeries in Video by Detecting Double Quantization. MM&Sec’09 Proceedings of the 11th ACM workshop on Multimedia and Security, 39‒48.

[5] Rosenfeld, K., Sencar, T., & Memon, N. A Study of the Robustness of PRNU-based Camera Identification,” Retrieved on November 1, 2014, from http://isis.poly.edu/~forensics/PAPERS/1 7.pdf

[6] McCloskey, S. (2008).Confidence Weighting for Sensor Fingerprinting. Honeywell Labs. Retrieved on November 1, 2014, from http://www.cim.mcgill.ca/~scott/papers/ WVU_2008.pdf

[7] Sencar, H. T., & Memnon, N. (2008).Overview of State-of-the-Art in Digital Image Forensics. Statistical Science and Interdisciplinary Research. World Scientific Press.

[8] Swaminathan, A., Wu, M., & Liu, K. J. Ray (May 2006). Non-Intrusive Forensic Analysis of Visual Sensors Using Output Images. Proc. of IEEE Conference on Acoustic, Speech and Signal Processing (ICASSP), 5, 401‒404.

[9] Retrieved on [date] from http://www.winsite.com/Multimedia/Imag e-Viewers/PRNU-Decompare

[10] YouTube, Statistics, Retrieved on November 1, 2014, from http://www.youtube.com/yt/press/statisti cs.html

[11] dDForum, homepage, Retrieved on November 1, 2014, from http://www.3dphoto.net/forum/index.php? topic=1034.0

[12] Ambarella™, Technology – The Ambarella Difference, Retrieved on November 1, 2014, from http://www.ambarella.com/technology/ana tomy-of-quality.html

[13] dDForum, homepage, Retrieved on November 1, 2014, from http://www.3dphoto.net/forum/index.php? topic=1034.0

[14] AVS Video Converter 9.0, homepage, Retrieved on November 1, 2014, from http://www.avs4you.com/AVS-VideoConverter.aspx?type=GoogleAdWordsSear ch&gclid=CPrH7JPPurwCFWYaOgodX3o A0A

[15] Grigoras, C. (2005). Digital Audio Recording Analysis – The Electric Network Frequency Criterion. International Journal of Speech Language and the Law, 12(1), 63–76.

[16] Acoustical Surfaces, Inc., homepage, Retrieved on November 1, 2014, from http://www.acousticalsurfaces.com/foam_s top/mel_comp.htm

[17] Detectus AB, Products, EMC Scanner, Retrieved on November 1, 2014, from http://detectus.se/products_emc.html

[18] Sonoma-Instrument.com, Specifications, 330 Broadband Scanner, Retrieved on November 1, 2014, from http://www.sonomainstrument.com/pdf/330ds.pdf

[19] Keepvid: Download Online, Retrieved on November 1, 2014, from www.keepvid.com



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