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Fast Imaging Sensor Identification

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Computational Collective Intelligence (ICCCI 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12876))

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Abstract

We consider identification of imaging devices by analysing images they produce. The problem is studied in the literature, yet the existing solutions are rather computationally demanding. We propose a high-speed algorithm for identification of imaging devices. The aim is to provide additional security by identification of legitimate imaging devices or an identification for forensics. The experimental evaluation confirms efficient identification of devices models and brands by the proposed algorithm, compared with the state-of-the-art method. Moreover, our algorithm is approximately two orders of magnitude faster, which is very important in resource-constrained IoT ecosystems or very large databases.

The project financed under the program of the Polish Minister of Science and Higher Education under the name “Regional Initiative of Excellence” in the years 2019–2022 project number 020/RID/2018/19, the amount of financing 12,000,000.00 PLN.

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Authors and Affiliations

  1. Department of Intelligent Computer Systems, Czȩstochowa University of Technology, al. Armii Krajowej 36, 42-200, Czȩstochowa, Poland

    Jarosław Bernacki & Rafał Scherer

Authors
  1. Jarosław Bernacki
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  2. Rafał Scherer
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Corresponding author

Correspondence to Rafał Scherer .

Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Democritus University of Thrace, Kimmeria, Xanthi, Greece

    Lazaros Iliadis

  3. University of Piraeus, Piraeus, Greece

    Ilias Maglogiannis

  4. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Bernacki, J., Scherer, R. (2021). Fast Imaging Sensor Identification. In: Nguyen, N.T., Iliadis, L., Maglogiannis, I., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2021. Lecture Notes in Computer Science(), vol 12876. Springer, Cham. https://doi.org/10.1007/978-3-030-88081-1_43

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  • DOI: https://doi.org/10.1007/978-3-030-88081-1_43

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-88080-4

  • Online ISBN: 978-3-030-88081-1

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