A Secure Chaotic DNA-Based Framework for Satellite Image Encryption

Abstract: With the growing use of satellite imaging in environmental monitoring, defense, and remote sensing applications, protecting satellite images during storage and transmission has become increasingly important. Unlike textual data, satellite images contain high spatial redundancy and strong correlations among neighboring pixels, which can limit the effectiveness of conventional encryption methods when applied directly. To address this issue, this study presents a chaotic DNA-based framework for satellite image encryption. The proposed approach combines logistic-map-based chaotic key generation with DNA-inspired encoding and XOR operations to enhance pixel-level confusion and diffusion. The method was evaluated on a grayscale satellite image using common statistical security measures, including information entropy, adjacent-pixel correlation, NPCR, and UACI. The reported results indicate that the encrypted image achieved high entropy, low correlation between adjacent pixels, and strong sensitivity to small changes in the input image. These findings suggest that the proposed framework provides a reasonable basis for secure satellite image encryption. Although the current evaluation is limited in scope, the method shows encouraging performance and offers a useful direction for further investigation on larger and more diverse satellite image datasets.

Asim Seedahmed Ali Osman, Ibrahim Rizqallah Alzahrani, Aeshah Khalil I Alotaibi, Adil Mahmoud Mohamed Mahmoud and Daifallah Zaid Alotaibe. “A Secure Chaotic DNA-Based Framework for Satellite Image Encryption”. International Journal of Advanced Computer Science and Applications (IJACSA) 17.5 (2026). http://dx.doi.org/10.14569/IJACSA.2026.0170551

@article{Osman2026,
title = {A Secure Chaotic DNA-Based Framework for Satellite Image Encryption},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2026.0170551},
url = {http://dx.doi.org/10.14569/IJACSA.2026.0170551},
year = {2026},
publisher = {The Science and Information Organization},
volume = {17},
number = {5},
author = {Asim Seedahmed Ali Osman and Ibrahim Rizqallah Alzahrani and Aeshah Khalil I Alotaibi and Adil Mahmoud Mohamed Mahmoud and Daifallah Zaid Alotaibe}
}