Publication:
Enhanced Least Significant Bit-Based Algorithms For Spatial Domain Image Steganography

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dc.contributor.authorAl Enzi, Abdalla Ramah
dc.date.accessioned2026-06-12T07:56:38Z
dc.date.available2026-06-12T07:56:38Z
dc.date.issued2025-06
dc.description.abstractIn digital image security, steganography conceals data within images using least significant bit (lsb) methods, which often compromise image quality. This research introduces three novel algorithms: pixel indices least significant bit (pilsb), semi-adaptive least significant bit (sdlsb), and reversible rewritable least significant bit (rrlsb), which aim to improve stego-image quality by minimizing the number of modified bits during the embedding process. The goal is to address the limitations of traditional lsb steganography, particularly issues of compromised security, reduced imperceptibility, and limited payload capacity. The methodology involves a comparative analysis of the three algorithms, measuring peak signal-to-noise ratio (psnr), mean squared error (mse), and structural similarity index (ssim) across different image and secret message sizes. Pilsb uses red and green lsbs for data embedding and blue lsbs for indexing, improving embedding efficiency. Sdlsb dynamically decomposes bytes based on color intensity to increase payload, while rrlsb employs reverse lsb in a two-stage process for indirect data embedding.
dc.identifier.urihttps://erepo.usm.my/handle/123456789/24369
dc.language.isoen
dc.subjectEnhanced Least Significant Bit-Based Algorithms For Spatial Domain Image Steganography
dc.titleEnhanced Least Significant Bit-Based Algorithms For Spatial Domain Image Steganography
dc.typeResource Types::text::thesis::doctoral thesis
dspace.entity.typePublication
oairecerif.author.affiliationUniversiti Sains Malaysia
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