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Applications of Deep Learning in Image Steganography

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  • Adrian Doroiman

    (Bucharest University of Economic Studies, Bucharest, Romania)

Abstract

The current paper presents the concept of steganography, with a focus on image steganography. It outlines a few relevant techniques for image steganography. Provides implementation details and a comparative evaluation of design and results. Proposes further research steps.

Suggested Citation

  • Adrian Doroiman, 2025. "Applications of Deep Learning in Image Steganography," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 3, pages 185-193.
    • Handle: RePEc:ddj:fseeai:y:2025:i:3:p:185-193
    DOI: https://doi.org/10.35219/eai15840409564
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    File URL: https://eia.feaa.ugal.ro/images/eia/2025_3/Doroiman.pdf
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    References listed on IDEAS

    as
    1. Richard Apau & Michael Asante & Frimpong Twum & James Ben Hayfron-Acquah & Kwame Ofosuhene Peasah, 2024. "Image steganography techniques for resisting statistical steganalysis attacks: A systematic literature review," PLOS ONE, Public Library of Science, vol. 19(9), pages 1-47, September.
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