Audio forgery detection based on max offsets for cross correlation between ENF and reference signal

Authors:
Yongjian Hu;Chang-Tsun Li;Zhisheng Lv;Bei-Bei Liu
Affiliations:
Department of Computer Science, University of Warwick, Coventry, UK,School of Electronic and Information Engineering, South China University of Technology, Guangzhou, P.R. China;Department of Computer Science, University of Warwick, Coventry, UK;School of Electronic and Information Engineering, South China University of Technology, Guangzhou, P.R. China;School of Electronic and Information Engineering, South China University of Technology, Guangzhou, P.R. China
Venue:
IWDW'12 Proceedings of the 11th international conference on Digital Forensics and Watermaking
Year:
2012

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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.