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Digital Forensics and Cyber Crime. 11th EAI International Conference, ICDF2C 2020, Boston, MA, USA, October 15-16, 2020, Proceedings

Research Article

Modelling GOP Structure Effects on ENF-Based Video Forensics

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  • @INPROCEEDINGS{10.1007/978-3-030-68734-2_7,
        author={Pasquale Ferrara and Gerard Draper-Gil and Ignacio Sanchez and Henrik Junklewitz and Laurent Beslay},
        title={Modelling GOP Structure Effects on ENF-Based Video Forensics},
        proceedings={Digital Forensics and Cyber Crime. 11th EAI International Conference, ICDF2C 2020, Boston, MA, USA, October 15-16, 2020, Proceedings},
        proceedings_a={ICDF2C},
        year={2021},
        month={2},
        keywords={Electric network frequency Video Compression GOP Signal processing Forensics},
        doi={10.1007/978-3-030-68734-2_7}
    }
    
  • Pasquale Ferrara
    Gerard Draper-Gil
    Ignacio Sanchez
    Henrik Junklewitz
    Laurent Beslay
    Year: 2021
    Modelling GOP Structure Effects on ENF-Based Video Forensics
    ICDF2C
    Springer
    DOI: 10.1007/978-3-030-68734-2_7
Pasquale Ferrara,*, Gerard Draper-Gil, Ignacio Sanchez, Henrik Junklewitz, Laurent Beslay
    *Contact email: pasquale.ferrara@ec.europa.eu

    Abstract

    Electricity is transported through the network as alternate current, usually at a carrier frequency (50/60 Hz) which is known as Electric Network Frequency (ENF). In practice, ENF fluctuates around the nominal value because of changes in the supply and demand of power over time. These fluctuations are conveyed by the light that is emitted by sources connected to the power grid. Captured by video recordings, such localized variations can be exploited as digital watermarks in order to determine the position of a video in time (e.g. timestamping) and space, as well as to verify its integrity. However, the encoded formats of acquired videos alter the shape of ENF extracted from video frames. This paper provides an analytical model for characterizing the effects of group of pictures (GOP) structure adopted by the most widespread video encoders. The model is assessed through an experimental evaluation campaign, by analyzing different working conditions and by showing how the information from the GOP can contribute to the extraction of ENF from video frames.

    Keywords
    Electric network frequency Video Compression GOP Signal processing Forensics
    Published
    2021-02-07
    Appears in
    SpringerLink
    http://dx.doi.org/10.1007/978-3-030-68734-2_7
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