sesa 18: e4

Research Article

Authenticating Video Feeds using Electric Network Frequency Estimation at the Edge

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  • @ARTICLE{10.4108/eai.4-2-2021.168648,
        author={Deeraj Nagothu and Yu Chen and Alexander Aved and Erik Blasch},
        title={Authenticating Video Feeds using Electric Network Frequency Estimation at the Edge},
        journal={EAI Endorsed Transactions on Security and Safety: Online First},
        volume={},
        number={},
        publisher={EAI},
        journal_a={SESA},
        year={2021},
        month={2},
        keywords={Video Data Authentication, Electrical Network Frequency (ENF) Estimation, Internet of Video Things (IoVT), Edge Computing, Visual Layer Backdoor Attacks},
        doi={10.4108/eai.4-2-2021.168648}
    }
    
  • Deeraj Nagothu
    Yu Chen
    Alexander Aved
    Erik Blasch
    Year: 2021
    Authenticating Video Feeds using Electric Network Frequency Estimation at the Edge
    SESA
    EAI
    DOI: 10.4108/eai.4-2-2021.168648
Deeraj Nagothu1, Yu Chen1,*, Alexander Aved2, Erik Blasch2
  • 1: Department of Electrical and Computer Engineering, Binghamton University, USA
  • 2: The U.S. Air Force Research Laboratory, USA
*Contact email: ychen@binghamton.edu

Abstract

Large scale Internet of Video Things (IoVT) supports situation awareness for smart cities; however, the rapid development in artificial intelligence (AI) technologies enables fake video/audio streams and doctored images to fool smart city security operators. Authenticating visual/audio feeds becomes essential for safety and security, from which an Electric Network Frequency (ENF) signal collected from the power grid is a prominent authentication mechanism. This paper proposes an ENF-based Video Authentication method using steady Superpixels (EVAS). Video superpixels group the pixels with uniform intensities and textures to eliminate the impacts from the fluctuations in the ENF estimation. An extensive experimental study validated the effectiveness of the EVAS system. Aiming at the environments with interconnected surveillance camera systems at the edge powered by an electricity grid, the proposed EVAS system achieved the design goal of detecting dissimilarities in the image sequences.