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Implementation and Performance Analysis of PVD Method in Concealing Encrypted Data on Images Hanif, Ardhan; Astuti, Nur Rochmah Dyah Puji; Aribowo, Eko
IJID (International Journal on Informatics for Development) Vol. 14 No. 1 (2025): IJID June
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

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Abstract

This research aims to secure text data by combining steganography and cryptography. The Pixel Value Differencing (PVD) method allows for higher data insertion capacity with minimal distortion, thereby increasing resistance to steganalysis. However, the PVD steganography method is vulnerable to variation in image areas and to the accuracy of Pixel Difference Histogram (PDH) analysis. In addition, this method is susceptible to statistical tools such as the chi-square and RS, which can be used to analyze the distribution of pixel value differences, allowing data to be detected. To address the limitations of the PVD method, we employed a cryptographic technique called XOR-VLSB, which combines XOR as the primary encryption method, Vigenère Cipher for key generation, and Least Significant Bit (LSB) for key embedding. The results showed that the fully encrypted data could be recovered and had good image quality, as indicated by the metric results, which included a low MSE value, a PSNR above 35 dB, and an SSIM value close to 1. In this study, the process of encrypting text data still uses a simple encryption algorithm, namely XOR. Future research may involve replacing cryptographic algorithms with AES, which offers stronger protection and better resistance to advanced security threats.
Studi Pendekatan Quality & Differential Analysis TerhadapKinerja Algoritma AES-CBC pada Enkripsi Gambar Gafur, Sartika; Aribowo, Eko
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 12 No 5: Oktober 2025
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2025125

Abstract

Penelitian ini mengeksplorasi pendekatan Quality & Differential Analysis untuk menilai kinerja algoritma AES-Cipher Block Chaining (AES-CBC) pada enkripsi gambar dengan resolusi 512 x 512 piksel. Algoritma AES-CBC dipilih karena kemampuannya menyediakan enkripsi blok yang aman dan efisien terhadap data berstruktur pada gambar berekstensi *.jpg, *.jpeg, *.png, *.gif, *.bmp, *.tiff, *.webp, *.heic, *.heif, *.svg, *.raw, *.psd, dan *.ico. Penelitian ini menggunakan tujuh metrik evaluasi yang komprehensif: Encryption Quality (MSE, RMSE, PSNR, SSIM) dan Differential Analysis (NPCR, UACI, CC), yang lebih komprehensif dibandingkan beberapa penelitian sebelumnya yang umumnya hanya menggunakan dua atau tiga metrik. Hasil penelitian menunjukkan bahwa algoritma AES-CBC mampu menghasilkan enkripsi gambar yang kuat, dengan nilai MSE dan RMSE sebesar 0.0, PSNR tak terhingga (inf dB), dan SSIM 1.0. Nilai NPCR berkisar antara 99.97% hingga 100%, UACI antara 49.87% hingga 50.26%, dan CC antara -0.0055 hingga 0.007, menunjukkan kemampuan algoritma dalam menangani perubahan diferensial. Penelitian ini memberikan wawasan mendalam tentang efektivitas algoritma AES-CBC dalam mengamankan file gambar dan menawarkan analisis menyeluruh tentang kualitas enkripsi dan ketahanannya terhadap serangan diferensial. Hasil penelitian ini diharapkan dapat berkontribusi pada pengembangan teknik enkripsi yang lebih aman di masa depan.   Abstract This research explores Quality & Differential Analysis approach to assess the performance of AES-Cipher Block Chaining (AES-CBC) algorithm on image encryption with 512 x 512 pixels resolution. The AES-CBC algorithm was chosen for its ability to provide secure and efficient block encryption of structured data in images with the extensions *.jpg, *.jpeg, *.png, *.gif, *.bmp, *.tiff, *.webp, *.heic, *.heif, *.svg, *.raw, *.psd, and *.ico. This research uses seven comprehensive evaluation metrics: Encryption Quality (MSE, RMSE, PSNR, SSIM) and Differential Analysis (NPCR, UACI, CC), which is more comprehensive than some previous studies that generally only use two or three metrics. The results show that the AES-CBC algorithm is able to produce strong image encryption, with MSE and RMSE values of 0.0, PSNR infinity (inf dB), and SSIM 1.0. NPCR values range from 99.97% to 100%, UACI between 49.87% to 50.26%, and CC between -0.0055 to 0.007, demonstrating the algorithm's ability to handle differential changes. This research provides an in-depth insight into the effectiveness of the AES-CBC algorithm in securing image files and offers a thorough analysis of its encryption quality and resistance to differential attacks. The results of this research are expected to contribute to the development of more secure encryption techniques in the future.