International Journal on Science and Technology

E-ISSN: 2229-7677     Impact Factor: 9.88

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 16 Issue 2 April-June 2025 Submit your research before last 3 days of June to publish your research paper in the issue of April-June.

To compare and analyze the effectiveness of Various state of the art StegnoGAN Methods

Author(s) A.Dharani, M.Lathika Sri, T.Muneeswari, J.Hemalatha, M.Sekar
Country India
Abstract Image steganography hides secret messages within images, aiming to conceal the message's existence. Traditional methods often lack robustness and visual quality. With deep learning, especially GANs, data hiding has become more effective. GANs enable seamless embedding of information while maintaining image realism, making them ideal for secure, imperceptible communication.
Keywords Data hiding, Steganography, Generative Adversarial Networks, Deep Learning,
Field Engineering
Published In Volume 16, Issue 2, April-June 2025
Published On 2025-05-07
DOI https://doi.org/10.71097/IJSAT.v16.i2.4735
Short DOI https://doi.org/g9hsps

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