DOI: https://doi.org/10.14710/jmasif.16.2.74537

Multi-Level Secure Image Cryptosystem Using Logistic Map Chaos: Entropy, Correlation, and 3D Histogram Validation

1Universitas Dian Nuswantoro, Indonesia

2Bowie State University, United States

Received: 16 Jun 2025; Revised: 3 Oct 2025; Accepted: 13 Oct 2025; Published: 6 Nov 2025.
Open Access Copyright (c) 2025 The authors. Published by Department of Informatics Universitas, Diponegoro
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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Abstract
This study proposes a multi-level image cryptosystem that combines password-derived SHA-256 key generation with a Logistic Map-based chaotic process. The framework supports three configurable modes, Speed, Balanced, and Security, allowing flexible adaptation to different application requirements. Performance evaluations indicate that the method achieves up to 27% faster encryption than AES for 1024×1024 images while preserving strong security properties. The scheme demonstrates high randomness with entropy values near 7.69 bits per pixel, negligible adjacent-pixel correlation (<0.01), and strong resistance to differential attacks (NPCR exceeding 99.6% and UACI around 33.4%). Decryption also preserves structural fidelity, with SSIM values consistently above 0.98, and scalability is ensured with support for images up to 2048×2048 pixels. When compared with recent chaos-based techniques, such as those reported by Arif et al. and Riaz et al., the proposed method exhibits superior entropy, enhanced adaptability through its multi-mode design, and broader resolution support. Extensive testing using entropy, correlation, PSNR, SSIM, XOR, and 3D histogram analyses further verifies the system’s robustness. These outcomes confirm the potential of the framework for real-time secure image communication, particularly in domains like IoT, healthcare imaging, and embedded systems
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Keywords: image encryption; Logistic Map; SHA-256; chaos theory; entropy analysis;

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Section: Research Article
Language : EN
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