Exploiting the Rolling Shutter Read-Out Time for ENF-Based Camera Identification

Ericmoore Ngharamike; Li-Minn Ang; Kah Phooi Seng; Mingzhong Wang

doi:10.3390/app13085039

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Exploiting the Rolling Shutter Read-Out Time for ENF-Based Camera Identification

Journal article

Open access

Peer reviewed

Exploiting the Rolling Shutter Read-Out Time for ENF-Based Camera Identification

Ericmoore Ngharamike, Li-Minn Ang, Kah Phooi Seng and Mingzhong Wang

Applied Sciences, Vol.13(8), pp.1-16

2023

DOI: https://doi.org/10.3390/app13085039

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Abstract

camera forensics

camera sensor types

electric network frequency (ENF)

ENF extraction

read-out time, Tro

rolling shutter mechanism

The electric network frequency (ENF) is a signal that varies over time and represents the frequency of the energy supplied by a mains power system. It continually varies around a nominal value of 50/60 Hz as a result of fluctuations over time in the supply and demand of power and has been employed for various forensic applications. Based on these ENF fluctuations, the intensity of illumination of a light source powered by the electrical grid similarly fluctuates. Videos recorded under such light sources may capture the ENF and hence can be analyzed to extract the ENF. Cameras using the rolling shutter sampling mechanism acquire each row of a video frame sequentially at a time, referred to as the read-out time ( Tro ) which is a camera-specific parameter. This parameter can be exploited for camera forensic applications. In this paper, we present an approach that exploits the ENF and the Tro to identify the source camera of an ENF-containing video of unknown source. The suggested approach considers a practical scenario where a video obtained from the public, including social media, is investigated by law enforcement to ascertain if it originated from a suspect’s camera. Our experimental results demonstrate the effectiveness of our approach.

Details

Title: Exploiting the Rolling Shutter Read-Out Time for ENF-Based Camera Identification
Authors: Ericmoore Ngharamike (Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and Engineering
Li-Minn Ang (Corresponding Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and Engineering
Kah Phooi Seng (Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and Engineering
Mingzhong Wang (Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and Engineering
Publication details: Applied Sciences, Vol.13(8), pp.1-16
Publisher: MDPI AG
Date published: 2023
DOI: 10.3390/app13085039
ISSN: 2076-3417
Copyright note: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Organisation Unit: School of Science, Technology and Engineering; Engage Research Lab
Language: English
Record Identifier: 99721798902621
Output Type: Journal article

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Collaboration types: Domestic collaboration; International collaboration
Web Of Science research areas: Chemistry, Multidisciplinary; Engineering, Multidisciplinary; Materials Science, Multidisciplinary; Physics, Applied