Penerapan Metode Least Significant Bit untuk Penyembunyian Pesan Rahasia dalam Gambar dengan Optimasi Ukuran File
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Yuliana, Rohmi Dyah Astuti, Ade Laelani, Linda Rassiyanti, Yusni Puspha Lestari, Ronal

Penerapan Metode Least Significant Bit untuk Penyembunyian Pesan Rahasia dalam Gambar dengan Optimasi Ukuran File

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Introduction

Penerapan metode least significant bit untuk penyembunyian pesan rahasia dalam gambar dengan optimasi ukuran file . Penelitian ini menerapkan steganografi LSB untuk menyembunyikan pesan rahasia dalam gambar. Evaluasi format PNG, WebP, ZIP menunjukkan PNG optimal untuk integritas pesan dan kualitas citra. Hindari kompresi lossy.

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Abstract

Steganografi merupakan teknik untuk menyembunyikan pesan rahasia dalam media digital guna menjaga kerahasiaan informasi. Penelitian ini menerapkan metode penyisipan pesan menggunakan algoritma Least Significant Bit (LSB), di mana pesan rahasia disisipkan langsung ke dalam bit-bit paling tidak signifikan dari piksel citra grayscale. Setelah proses penyisipan, citra stego disimpan dalam tiga format berbeda—PNG, WebP, dan ZIP—untuk mengevaluasi dampak kompresi terhadap integritas pesan dan kualitas citra. Evaluasi dilakukan berdasarkan empat parameter: ukuran file, degradasi kualitas citra (PSNR), kesamaan struktur visual (SSIM), dan keberhasilan ekstraksi pesan. Hasil menunjukkan bahwa format PNG mampu mempertahankan kualitas citra dan integritas pesan secara optimal (PSNR 75,58 dB, SSIM 1,0000). Sebaliknya, kompresi lossy pada WebP mengganggu bit pesan sehingga menyebabkan pesan rusak. Format ZIP terbukti dapat mempertahankan file stego secara utuh. Penelitian ini menunjukan bahwa steganografi berbasis Least Significant Bit tetap efektif bila dikombinasikan dengan format gambar lossless. Format lossy seperti WebP tidak disarankan karena berisiko merusak data.


Review

This paper presents a focused investigation into the application of the Least Significant Bit (LSB) method for embedding secret messages within grayscale images, with a particular emphasis on optimizing file size and preserving message integrity through different storage formats. The core methodology involves directly modifying the least significant bits of image pixels to embed the secret data. A commendable aspect of this research is the systematic evaluation of the stego image's robustness when saved in three distinct post-embedding formats—PNG, WebP, and ZIP—which addresses a crucial practical consideration in steganographic applications. The chosen evaluation parameters, including file size, PSNR, SSIM, and message extraction success, provide a comprehensive framework for assessing performance. The experimental results yield clear and significant insights into the interplay between steganography and image compression. The study unequivocally demonstrates that PNG, a lossless compression format, excels in maintaining both the visual quality of the stego image (achieving an impressive PSNR of 75.58 dB and SSIM of 1.0000) and, critically, the integrity of the hidden message. Conversely, the findings highlight the inherent conflict between LSB steganography and lossy compression formats like WebP, where the compression artifacts inevitably corrupt the embedded message, rendering the steganographic effort futile. The inclusion of ZIP as a packaging format further reinforces the necessity of lossless handling for successful message retrieval, as it preserves the stego file intact. Overall, this research delivers a straightforward yet impactful conclusion: the effectiveness of LSB-based steganography is highly contingent upon the post-embedding storage format. It unequivocally demonstrates that lossless formats are essential for preserving data integrity when using simple bit-replacement methods. While the paper clearly identifies the vulnerability to lossy compression, it offers valuable practical guidance for practitioners and researchers in digital steganography, underscoring the critical need to select appropriate file formats to ensure successful secret communication. The findings are well-supported by quantitative metrics and provide a clear cautionary tale regarding the use of lossy compression with basic LSB schemes.


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