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Location Forensics Analysis Using ENF Sequences Extracted from Power and Audio Recordings
Electrical network frequency (ENF) is the signature of a power distribut...
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Implementation of ASK, FSK and PSK with BER vs. SNR comparison over AWGN channel
This paper mainly discusses about three basic digital modulation process...
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Location Forensics of Media Recordings Utilizing Cascaded SVM and Pole-matching Classifiers
Information regarding the location of power distribution grid can be ext...
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Analysis of Rolling Shutter Effect on ENF based Video Forensics
ENF is a time-varying signal of the frequency of mains electricity in a ...
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A fast subsampling method for estimating the distribution of signal-to-noise ratio statistics in nonparametric time series regression models
Signal-to-noise ratio (SNR) statistics play a central role in many appli...
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A Cross-Verification Approach for Protecting World Leaders from Fake and Tampered Audio
This paper tackles the problem of verifying the authenticity of speech r...
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Detecting the Presence of ENF Signal in Digital Videos: a Superpixel based Approach
ENF (Electrical Network Frequency) instantaneously fluctuates around its...
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Reliability of Power System Frequency on Times-Stamping Digital Recordings
Power system frequency could be captured by digital recordings and extracted to compare with a reference database for forensic time-stamp verification. It is known as the electric network frequency (ENF) criterion, enabled by the properties of random fluctuation and intra-grid consistency. In essence, this is a task of matching a short random sequence within a long reference, and the reliability of this criterion is mainly concerned with whether this match could be unique and correct. In this paper, we comprehensively analyze the factors affecting the reliability of ENF matching, including length of test recording, length of reference, temporal resolution, and signal-to-noise ratio (SNR). For synthetic analysis, we incorporate the first-order autoregressive (AR) ENF model and propose an efficient time-frequency domain (TFD) noisy ENF synthesis method. Then, the reliability analysis schemes for both synthetic and real-world data are respectively proposed. Through a comprehensive study we reveal that while the SNR is an important external factor to determine whether time-stamp verification is viable, the length of test recording is the most important inherent factor, followed by the length of reference. However, the temporal resolution has little impact on the matching process.
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