ENHANCED IMAGE STEGANOGRAPHY: LSB SUBSTITUTION WITH RUN-LENGTH ENCODED SECRET DATA

Image steganography has emerged as a vital technique for secure communication by concealing sensitive information within innocuous digital media. This study proposes an enhanced image steganography method that integrates Least Significant Bit (LSB) substitution with run-length encoding (RLE) of the secret data to improve embedding efficiency and reduce detectability. By applying run-length encoding prior to embedding, the secret message is compressed, enabling a greater volume of information to be hidden within the cover image while maintaining minimal perceptual distortion. The proposed approach adaptively selects embedding regions based on local image characteristics to further increase imperceptibility and robustness against steganalysis. Experimental results demonstrate that the method achieves higher peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) compared to conventional LSB substitution techniques without compression. This research highlights the potential of combining data compression and adaptive embedding strategies to advance the state of image steganography, offering a practical solution for secure data hiding in modern digital communication environments.

Authors

Institutions

Publication Details

Journal
International Journal of Intelligent Data and Machine Learning
Published
2025-04-01
DOI
https://doi.org/10.55640/ijidml-v02i04-01
Primary Topic
Advanced Steganography and Watermarking Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

ENHANCED IMAGE STEGANOGRAPHY: LSB SUBSTITUTION WITH RUN-LENGTH ENCODED SECRET DATA

María Eugenia González
International Journal of Intelligent Data and Machine Learning
Advanced Steganography and Watermarking Techniques
article

ENHANCED IMAGE STEGANOGRAPHY: LSB SUBSTITUTION WITH RUN-LENGTH ENCODED SECRET DATA

María Eugenia González
article en

Abstract

Image steganography has emerged as a vital technique for secure communication by concealing sensitive information within innocuous digital media. This study proposes an enhanced image steganography method that integrates Least Significant Bit (LSB) substitution with run-length encoding (RLE) of the secret data to improve embedding efficiency and reduce detectability. By applying run-length encoding prior to embedding, the secret message is compressed, enabling a greater volume of information to be hidden within the cover image while maintaining minimal perceptual distortion. The proposed approach adaptively selects embedding regions based on local image characteristics to further increase imperceptibility and robustness against steganalysis. Experimental results demonstrate that the method achieves higher peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) compared to conventional LSB substitution techniques without compression. This research highlights the potential of combining data compression and adaptive embedding strategies to advance the state of image steganography, offering a practical solution for secure data hiding in modern digital communication environments.

International Journal of Intelligent Data and Machine LearningVol. 2(04)
Instituto do Sono (BR)
Openalex Percentile: Top 86%
Advanced Steganography and Watermarking Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

ENHANCED IMAGE STEGANOGRAPHY: LSB SUBSTITUTION WITH RUN-LENGTH ENCODED SECRET DATA — María Eugenia González · International Journal of Intelligent Data and Machine Learning (2025) | TGRS Research Map | TGRS