Authors :
Mujittaba Bature; Abubakar Bello Lawal; Tanimu Lawal
Volume/Issue :
Volume 11 - 2026, Issue 7 - July
Google Scholar :
https://tinyurl.com/4ycvvnxh
Scribd :
https://tinyurl.com/sf5n5xca
DOI :
https://doi.org/10.38124/ijisrt/26jul188
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
The increasing demand for secure communication over public networks has intensified research on information
hiding techniques capable of protecting sensitive information from unauthorized access. Image steganography achieves this
objective by concealing secret information within digital images while preserving the visual appearance of the cover image.
Among the numerous image steganographic techniques, the Least Significant Bit (LSB) method is widely adopted because
of its simplicity, high embedding capacity, and low computational complexity. However, its sequential embedding
mechanism makes it susceptible to steganalysis and statistical attacks. To address this limitation, pseudorandom embedding
techniques distribute secret information randomly throughout the cover image using a shared secret key, thereby improving
security and imperceptibility. This paper presents a comparative performance analysis of the LSB and Pseudorandom
Encoding techniques for secure image steganography. Both techniques were implemented in MATLAB using identical cover
images and secret messages to ensure an unbiased evaluation. Performance was assessed using Peak Signal-to-Noise Ratio
(PSNR), Mean Square Error (MSE), Signal-to-Noise Ratio (SNR), embedding capacity, and visual image quality.
Experimental results demonstrate that although both techniques effectively conceal secret information with negligible
perceptual degradation, the Pseudorandom Encoding technique consistently produces higher PSNR values and lower
distortion than the conventional LSB method. Furthermore, the random distribution of embedded data significantly
improves resistance to unauthorized detection while maintaining comparable embedding capacity. The findings confirm
that pseudorandom embedding provides a more secure and robust alternative to sequential LSB steganography for digital
image information hiding.
Keywords :
Image Steganography, Least Significant Bit (LSB), Pseudorandom Encoding, Information Hiding, MATLAB, PSNR, MSE, SNR, Image Security.
References :
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The increasing demand for secure communication over public networks has intensified research on information
hiding techniques capable of protecting sensitive information from unauthorized access. Image steganography achieves this
objective by concealing secret information within digital images while preserving the visual appearance of the cover image.
Among the numerous image steganographic techniques, the Least Significant Bit (LSB) method is widely adopted because
of its simplicity, high embedding capacity, and low computational complexity. However, its sequential embedding
mechanism makes it susceptible to steganalysis and statistical attacks. To address this limitation, pseudorandom embedding
techniques distribute secret information randomly throughout the cover image using a shared secret key, thereby improving
security and imperceptibility. This paper presents a comparative performance analysis of the LSB and Pseudorandom
Encoding techniques for secure image steganography. Both techniques were implemented in MATLAB using identical cover
images and secret messages to ensure an unbiased evaluation. Performance was assessed using Peak Signal-to-Noise Ratio
(PSNR), Mean Square Error (MSE), Signal-to-Noise Ratio (SNR), embedding capacity, and visual image quality.
Experimental results demonstrate that although both techniques effectively conceal secret information with negligible
perceptual degradation, the Pseudorandom Encoding technique consistently produces higher PSNR values and lower
distortion than the conventional LSB method. Furthermore, the random distribution of embedded data significantly
improves resistance to unauthorized detection while maintaining comparable embedding capacity. The findings confirm
that pseudorandom embedding provides a more secure and robust alternative to sequential LSB steganography for digital
image information hiding.
Keywords :
Image Steganography, Least Significant Bit (LSB), Pseudorandom Encoding, Information Hiding, MATLAB, PSNR, MSE, SNR, Image Security.