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An audio tampering detection framework for low SNR conditions based on modified CZT
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An audio tampering detection framework for low SNR conditions based on modified CZT
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Journal Article
An audio tampering detection framework for low SNR conditions based on modified CZT
2025
Overview
Extracting the electric network frequency (ENF) from digital audio signals is a crucial means of forensic evidence. However, ENF signal extraction is susceptible to noise, making it challenging to establish a reliable matching relationship with the reference frequency database, especially under low signal-to-noise ratio (SNR) conditions. To solve this problem, an ENF extraction and tampering detection framework (ENF-ETD) for low SNR conditions is proposed in this article. Firstly, a modified Chirp Z-transform (MCZT) method is proposed to extract the ENF signal in digital audio. Subsequently, by comparing with the actual grid frequency, the Pearson correlation coefficient (PCC) and Euclidean distance (ED) are used to evaluate the accuracy of ENF estimation and determine whether the audio has been tampered with. Finally, the simulations and hardware-based experiments verify the proposed ENF-ETD framework’s effectiveness in noise immunity and digital audio tampering detection.
•To improve the representation ability of ENF components, a modified Chirp Z-transform (MCZT) method is proposed.•An ENF extraction and tampering detection (ENF-ETD) framework for low SNR digital audio signal is proposed.•Simulations are conducted to analyze the performance of the MCZT method for ENF extraction under different SNR conditions.•The different experimental results show that the framework has superior performance compared with some advanced methods.
Publisher
Elsevier B.V,Elsevier Limited
Subject
/ Methods
