Fast method for ENF database build and search

Pop, Gheorghe Ioan; Drăghicescu, Dragoș; Burileanu, Dragoş; Cucu, Horia; Burileanu, Corneliu

doi:10.1109/sped.2017.7990447

Cited by 4 publications

(2 citation statements)

References 6 publications

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“…In summary, the EV-ENFD ENF and E-ENF traces, the EV-ENFD also includes the corresponding ground-truth ENF reference for each set. We use a computer sound card to directly record the grid voltage changes after a step-down transformer, according to the works in [5,22]. An STFT with a 16-second time window and 1-second step (overlapped by 15 seconds) is used to obtain the ENF reference.…”

Section: Dataset and Experimental Settingsmentioning

confidence: 99%

Spatial and temporal variability of PM2.5 concentration in China

Jiao

Zhao

et al. 2016

Wuhan Univ. J. Nat. Sci.

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Most of the artificial lights fluctuate in response to the grid's alternating current and exhibit subtle variations in terms of both intensity and spectrum, providing the potential to estimate the Electric Network Frequency (ENF) from conventional frame-based videos. Nevertheless, the performance of Video-based ENF (V-ENF) estimation largely relies on the imaging quality and thus may suffer from significant interference caused by non-ideal sampling, motion, and extreme lighting conditions. In this paper, we show that the ENF can be extracted without the above limitations from a new modality provided by the so-called event camera, a neuromorphic sensor that encodes the light intensity variations and asynchronously emits events with extremely high temporal resolution and high dynamic range. Specifically, we first formulate and validate the physical mechanism for the ENF captured in events, and then propose a simple yet robust Event-based ENF (E-ENF) estimation method through mode filtering and harmonic enhancement. Furthermore, we build an Event-Video ENF Dataset (EV-ENFD) that records both events and videos in diverse scenes. Extensive experiments on EV-ENFD demonstrate that our proposed E-ENF method can extract more accurate ENF traces, outperforming the conventional V-ENF by a large margin, especially in challenging environments with object motions and extreme lighting conditions. The code and dataset are available at https://xlxcreater.github.io/E-ENF/.

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Section: Dataset and Experimental Settingsmentioning

confidence: 99%

Spatial and temporal variability of PM2.5 concentration in China

Jiao

Zhao

et al. 2016

Wuhan Univ. J. Nat. Sci.

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“…Second, determining whether a media's ENF sequence matches all potential ENF sequences may require a high computation cost, based on the information initially available about the recording. A solution to this problem is proposed in [110]. Third, this application presupposes that the time and place where the media recording in question took place already have its reference ENF measured.…”

Section: Initial Studies On Enf-based Forensic Analysis [4] -[7]mentioning

confidence: 99%

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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Power Signature for Multimedia Forensics

Hajj-Ahmad

Wong

Choi

et al. 2022

Multimedia Forensics

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There has been an increasing amount of work surrounding the Electric Network Frequency (ENF) signal, an environmental signature captured by audio and video recordings made in locations where there is electrical activity. ENF is the frequency of power distribution networks, 60 Hz in most of the Americas and 50 Hz in most other parts of the world. The ubiquity of this power signature and the appearance of its traces in media recordings motivated its early application toward time–location authentication of audio recordings. Since then, more work has been done toward utilizing this signature for other forensic applications, such as inferring the grid in which a recording was made, as well as applications beyond forensics, such as temporally synchronizing media pieces. The goal of this chapter is to provide an overview of the research work that has been done on the ENF signal and to provide an outlook for the future.

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Fast method for ENF database build and search

Cited by 4 publications

References 6 publications

Spatial and temporal variability of PM2.5 concentration in China

Spatial and temporal variability of PM2.5 concentration in China

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

Power Signature for Multimedia Forensics

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