Blackman–Tukey spectral estimation and electric network frequency matching from power mains and speech recordings

Karantaidis, Georgios; Kotropoulos, Constantine

doi:10.1049/sil2.12039

Cited by 6 publications

(3 citation statements)

References 59 publications

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“…In order to further increase the detection accuracy and robustness of audio tamper methods based on ENF, some scholars study the characteristics of ENF to obtain better features. Karantaidis (Karantaidis & Kotropoulos, 2021) added a customized lag Window to the Blackman-Tukey acoustic spectrum estimation method to reduce the interference of speech content, making the estimated ENF more accurate. Guang Hua (Hua & Zhang, 2019) proposed a robust filtering algorithm (RFA) to enhance ENF signals in audio, making the extracted ENF signals more accurate.…”

Section: Research On Tamper Detection Based On Electronic Network Fre...mentioning

confidence: 99%

Audio Tampering Forensics Based on Representation Learning of ENF Phase Sequence

Zeng

Yang

Wang

et al. 2022

International Journal of Digital Crime and Forensics

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This paper proposes an audio tampering detection method based on the ENF phase and BI-LSTM network from the perspective of temporal feature representation learning. First, the ENF phase is obtained by discrete Fourier transform of ENF component in audio. Second, the ENF phase is divided into frames to obtain ENF phase sequence characterization, and each frame is represented as the change information of the ENF phase in a period. Then, the BI-LSTM neural network is used to train and output the state of each time step, and the difference information between real audio and tampered audio is obtained. Finally, these differences were fitted and dimensionally reduced by the fully connected network and classified by the Softmax classifier. Experimental results show that the performance of this method is better than the state-of-the-art approaches.

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Section: Research On Tamper Detection Based On Electronic Network Fre...mentioning

confidence: 99%

Audio Tampering Forensics Based on Representation Learning of ENF Phase Sequence

Zeng

Yang

Wang

et al. 2022

International Journal of Digital Crime and Forensics

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“…Afterward, the prevalent frequency of each segment is estimated by spectral estimation. Frequently, a quadratic interpolation is used to overcome the interference that hinders the entire procedure and results in more precise ENF estimation [5,9]. Here, the estimated ENF signal f is calculated by employing shifts of 1 s (i.e., S = 1).…”

Section: Enf Estimationmentioning

confidence: 99%

“…There, a weighted linear prediction approach was also employed for ENF estimation. In [9], a lag window was designed to offer an optimal trade-off between smearing and leakage by maximizing the relative energy in the main lobe of the window. It was incorporated in the Blackman-Tukey method, offering accurate ENF estimation with low computational requirements.…”

Section: Introductionmentioning

confidence: 99%

An Automated Approach for Electric Network Frequency Estimation in Static and Non-Static Digital Video Recordings

Karantaidis

Kotropoulos

2021

J. Imaging

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Electric Network Frequency (ENF) is embedded in multimedia recordings if the recordings are captured with a device connected to power mains or placed near the power mains. It is exploited as a tool for multimedia authentication. ENF fluctuates stochastically around its nominal frequency at 50/60 Hz. In indoor environments, luminance variations captured by video recordings can also be exploited for ENF estimation. However, the various textures and different levels of shadow and luminance hinder ENF estimation in static and non-static video, making it a non-trivial problem. To address this problem, a novel automated approach is proposed for ENF estimation in static and non-static digital video recordings. The proposed approach is based on the exploitation of areas with similar characteristics in each video frame. These areas, called superpixels, have a mean intensity that exceeds a specific threshold. The performance of the proposed approach is tested on various videos of real-life scenarios that resemble surveillance from security cameras. These videos are of escalating difficulty and span recordings from static ones to recordings, which exhibit continuous motion. The maximum correlation coefficient is employed to measure the accuracy of ENF estimation against the ground truth signal. Experimental results show that the proposed approach improves ENF estimation against the state-of-the-art, yielding statistically significant accuracy improvements.

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ENF Based Digital Multimedia Forensics: Survey, Application, Challenges and Future Work

Ngharamike,

Ang,

Seng

et al. 2023

IEEE Access

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The electric network frequency (ENF) represents the transmission frequency of the electrical grid and fluctuates constantly around 50 Hz or 60 Hz, subject to the region. This constant fluctuation, caused by the continuous mismatch in power demand and supply, makes the ENF a unique signature, which can be utilized for several applications. According to studies, the ENF may be intrinsically implanted in audio recordings captured by digital audio recorders (e.g., microphone-based voice recorder) plugged into the mains supply or are situated close to sources of power and power transmission cable due to electromagnetic field interference originated from power source or acoustic hum and mechanical vibrations emitted by electrically operated devices such as regular household appliances. Recent studies further observed that video recordings made under an illumination source powered by main power can pick up the ENF signal. Following this discovery, several research efforts have been invested towards successful and accurate extraction of the ENF signal, and utilizing the ENF signal retrieved for several applications, including time stamp verification, audio/video authentication, location of recording estimation, power grid identification, estimation of camera read-out time, and video record synchronization. To the best of our knowledge, there has been no comprehensive survey on ENF-based multimedia forensics. Thus, in this paper, we present a comprehensive survey of studies conducted in this field, identifying several application specifics, current challenges, and future research directions.INDEX TERMS Electric network frequency (ENF), ENF detection, ENF estimation, audio and video forensic, ENF applications

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Blackman–Tukey spectral estimation and electric network frequency matching from power mains and speech recordings

Cited by 6 publications

References 59 publications

Audio Tampering Forensics Based on Representation Learning of ENF Phase Sequence

Audio Tampering Forensics Based on Representation Learning of ENF Phase Sequence

An Automated Approach for Electric Network Frequency Estimation in Static and Non-Static Digital Video Recordings

ENF Based Digital Multimedia Forensics: Survey, Application, Challenges and Future Work

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