A Desktop-Based Digital Image Encryption System Using The Lorenz Chaotic Map

Authors

  • Makmun Makmun Department Informatic Technic, Faculty of Industry Technology, Gunadarma University, Indonesia

DOI:

https://doi.org/10.51601/ijse.v6i1.459

Abstract

The increasing use of digital images in communication, healthcare, and information systems has raised the need for effective image security mechanisms. Conventional encryption methods are often less suitable for image data because of its large size and high correlation among adjacent pixels. Therefore, chaos-based cryptography has gained attention due to its sensitivity to initial conditions and ability to generate highly random sequences. This study aims to develop and evaluate a desktop-based digital image encryption application using the Lorenz System Chaotic Map to ensure image confidentiality and accurate reconstruction. This study employed a quantitative experimental approach in the form of a computational experiment. Data were collected through direct testing using RGB and grayscale images with different dimensions and formats, including .jpg, .png, and .bmp. The system was implemented in a desktop environment and evaluated using processing time, histogram analysis, Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), and key sensitivity analysis. The results show that the proposed system successfully transformed original images into visually unrecognizable encrypted images and reconstructed them perfectly during decryption. The encrypted images exhibited more uniform histogram distributions and low PSNR values, while the decrypted images showed zero MSE and infinite PSNR, indicating lossless recovery. The system also demonstrated high sensitivity to small key changes. These findings imply that the proposed method is effective for digital image protection in practical applications. The originality of this study lies in integrating a Lorenz-based encryption algorithm into a user-oriented desktop application equipped with built-in evaluation features.

Downloads

Download data is not yet available.

References

[1] W. H. O. WHO, "Global Strategy on Digital Health," 2024.

[2] P. Ewoh and T. Vartiainen, "Vulnerability to cyberattacks and sociotechnical solutions for health care systems: Systematic review," Journal of Medical Internet Research, vol. 26, p. e46904, 2024, doi: 10.2196/46904.

[3] M. Sajitha and S. Mathew, "A Review of Chaos-Based Image Encryption Techniques," Multimedia Tools and Applications, vol. 81, pp. 16827-16867, 2022, doi: 10.1007/s11042-021-11468-2.

[4] J. Pool, S. Akhlaghpour, F. Fatehi, and A. Burton-Jones, "A systematic analysis of failures in protecting personal health data: A scoping review," International Journal of Information Management, vol. 74, p. 102719, 2024, doi: 10.1016/j.ijinfomgt.2023.102719.

[5] A. S. Ahmad and K. H. Santoso, "The Urgency of Establishing AI Regulations to Ensure Legal Certainty and AI Ethics in Responding to Challenges Digitalization in Indonesia," International Journal of Science and Environment (IJSE), vol. 6, no. 1, pp. 366-371, 2026, doi: 10.51601/ijse.v6i1.353.

[6] Y. Alghamdi and A. Munir, "Image encryption algorithms: A survey of design and evaluation metrics," Journal of Cybersecurity and Privacy, vol. 4, no. 1, pp. 126-152, 2024, doi: 10.3390/jcp4010007.

[7] U. Zia et al., "Survey on image encryption techniques using chaotic maps in spatial, transform and spatiotemporal domains," International Journal of Information Security, vol. 21, no. 4, pp. 917-935, 2022, doi: 10.1007/s10207-022-00588-5.

[8] Y. Zhang, X. Wang, L. Liu, and Z. Zhang, "A Chaotic Image Encryption Algorithm Based on Permutation-Diffusion Structure," Nonlinear Dynamics, vol. 78, pp. 2021-2032, 2014, doi: 10.1007/s11071-014-1563-3.

[9] Y. Zhou, L. Bao, and C. L. P. Chen, "A New 1D Chaotic System for Image Encryption," Signal Processing, vol. 97, pp. 172-182, 2014, doi: 10.1016/j.sigpro.2013.11.008.

[10] A. Dinu and M. Frunzete, "Image encryption using chaotic maps: Development, application, and analysis," Mathematics, vol. 13, no. 16, p. 2588, 2025, doi: 10.3390/math13162588.

[11] B. Zhang and L. Liu, "Chaos-based image encryption: Review, application, and challenges," Mathematics, vol. 11, no. 11, p. 2585, 2023, doi: 10.3390/math11112585.

[12] F. Masood et al., "A lightweight chaos-based medical image encryption scheme using random shuffling and XOR operations," Wireless Personal Communications, vol. 127, no. 2, pp. 1405-1432, 2022, doi: 10.1007/s11277-021-08584-z.

[13] I. Yasser, F. Khalifa, M. A. Mohamed, and B. B. Samir, "A new image encryption scheme based on hybrid chaotic maps," Complexity, vol. 2020, p. 9597619, 2020, doi: 10.1155/2020/9597619.

[14] H. Wen, Y. Lin, S. Kang, X. Zhang, and K. Zou, "Secure image encryption algorithm using chaos-based block permutation and weighted bit planes chain diffusion," iScience, vol. 27, p. 108610, 2024, doi: 10.1016/j.isci.2023.108610.

[15] N. Yang, S. Zhang, M. Bai, and S. Li, "Medical image encryption based on Josephus traversing and hyperchaotic Lorenz system," Journal of Shanghai Jiaotong University (Science), vol. 29, pp. 91-108, 2024, doi: 10.1007/s12204-022-2555-x.

[16] X. Zhang, G. Man, R. Gao, C. Dai, and Q. Meng, "An image encryption method based on improved Lorenz chaotic system and Galois field," Applied Mathematics and Computation, vol. 472, p. 128623, 2024, doi: 10.1016/j.amc.2024.128623.

[17] Y. Sang, J. Sang, and M. S. Alam, "Image encryption based on logistic chaotic systems and deep autoencoder," Pattern Recognition Letters, vol. 153, pp. 59-66, 2022, doi: 10.1016/j.patrec.2021.11.025.

Downloads

Published

2026-03-29

How to Cite

Makmun, M. (2026). A Desktop-Based Digital Image Encryption System Using The Lorenz Chaotic Map. International Journal of Science and Environment (IJSE), 6(1), 1279–1288. https://doi.org/10.51601/ijse.v6i1.459