ENF analysis on recaptured audio recordings

2013 IEEE International Conference on Acoustics, Speech and Signal Processing Pub Date : 2013-05-26 DOI:10.1109/ICASSP.2013.6638212

Hui Su, Ravi Garg, Adi Hajj-Ahmad, Min Wu

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引用次数: 30

Abstract

Electric Network Frequency (ENF) based forensic analysis is a promising tool for timestamp authentication and forgery detection in such multimedia recordings as audios and videos. ENF signal is embedded in an audio recording due to electromagnetic interference from the power lines. The time of creation of a multimedia recording can be determined by comparing the ENF signal embedded in the recording with a reference ENF database collected from the power grid. In this paper, we conduct a study of the effect of recapturing of audio recordings on the ENF embedding. We demonstrate that recaptured audio recordings pick up two ENF signals: the content ENF signal which is inherited from the original audio recording; and the recapturing ENF signal which is embedded from the recapturing process. Conventional ENF signal extraction techniques on such recordings may fail when the two ENF signals are at the same nominal value. A decorrelation algorithm is proposed to extract the content ENF signal and the recapturing ENF signal. The experimental results show the effectiveness of the proposed method in the estimation of both the ENF signals.

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对重新捕获的录音进行ENF分析

基于电子网络频率(ENF)的取证分析是一种很有前途的时间戳认证和伪造检测工具，可用于音频和视频等多媒体记录。由于电力线的电磁干扰，ENF信号被嵌入音频记录中。创建多媒体记录的时间可以通过将记录中嵌入的ENF信号与从电网收集的参考ENF数据库进行比较来确定。在本文中，我们研究了音频重捕获对ENF嵌入的影响。我们证明，重新捕获的音频记录拾取两个ENF信号:从原始音频记录继承的内容ENF信号;以及从所述捕获过程中嵌入的重捕获ENF信号。当两个ENF信号处于相同的标称值时，传统的ENF信号提取技术可能会失败。提出了一种提取内容ENF信号和重捕获ENF信号的去相关算法。实验结果表明，该方法对两种ENF信号的估计都是有效的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2013 IEEE International Conference on Acoustics, Speech and Signal Processing

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