Abstract
The electric network frequency (ENF) is likely to be embedded in audio signals when the electronic recording devices are connected to electric power lines. If an audio signal is edited, the embedded ENF will be altered inevitably. In order to assess audio authenticity, this paper proposes a new method based on the max offset for cross correlation between the extracted ENF and the reference signal. By comparing the max offsets on a block-by-block basis, we can determine whether the audio signal in question was digitally edited as well as the location at which the editing manipulation occurs. The validity and effectiveness of our method have been verified by experiments on both synthetic composite signals and real-world audio signals.
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References
Sanders, R.W.: Digital authenticity using the electric network frequency. In: Proc. AES 33rd Int. Conf. Audio Forensic, Theory and Practice, Denver, CO (2008)
Maher, R.: Audio forensic examination: Authenticity, enhancement, and interpretation. IEEE Signal Processing Magazine 26(2), 84–94 (2009)
Grigoras, C.: Digital audio recording analysis: The electric network frequency (ENF) criterion. Speech Language Law 12(1), 63–76 (2005)
Kajstura, M., Trawinska, A., Hebenstreit, J.: Application of the Electrical Network Frequency (ENF) Criterion: A case of a digital recording. Forensic Science International 155(2), 165–171 (2005)
Grigoras, C.: Applications of ENF criterion in forensic audio, video, computer and telecommunication analysis. Forensic Science International 167(3), 136–145 (2007)
Huijbregtse, M., Geradts, Z.: Using the ENF criterion for determining the time of recording of short digital audio recordings. Computational Forensics, 116–124 (2009)
Nicolalde, D.P., Apolinario, J.A.: Evaluating digital audio authenticity with spectral distances and ENF phase change. In: 2009 IEEE International Conference on Acoustics, Speech and Signal Processing, Taipei, Taiwan, pp. 1417–1420 (2009)
Nicolalde Rodriguez, D.P., Apolinario, J.A., Biscainho, L.W.P.: Audio Authenticity: Detecting ENF Discontinuity with High Precision Phase Analysis. IEEE Transactions on Information Forensics and Security 5(3), 534–543 (2010)
Ortega-GarcÃa, J., González-RodrÃguez, J., Marrero-Aguiar, V.: AHUMADA, a large speech corpus in Spanish for speaker characterization and identification. Elsevier Speech Communication 31, 255–264 (2000)
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Hu, Y., Li, CT., Lv, Z., Liu, BB. (2013). Audio Forgery Detection Based on Max Offsets for Cross Correlation between ENF and Reference Signal. In: Shi, Y.Q., Kim, HJ., Pérez-González, F. (eds) The International Workshop on Digital Forensics and Watermarking 2012. IWDW 2012. Lecture Notes in Computer Science, vol 7809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40099-5_21
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DOI: https://doi.org/10.1007/978-3-642-40099-5_21
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