Medical image encryption based on four-dimensional chaotic system and DNA coding

To address the security challenges of medical images during network transmission and remote storage, this paper proposes a high-security image encryption algorithm that combines a four-dimensional Lorenz hyperchaotic system with DNA coding. The proposed method first utilizes a SHA-256 hash of the plaintext image to generate sensitive initial conditions, which are then used to drive the 4D Lorenz system to produce chaotic sequences. A Zigzag scan is employed to perform pixel-level permutation, followed by dynamic DNA encoding rules guided by the chaotic system. A DNA-XNOR diffusion process and cascading bit-level diffusion are introduced to enhance nonlinear confusion and global diffusion. Experimental results on various medical images demonstrate that the proposed algorithm achieves high information entropy, significantly reduces pixel correlation, and reaches NPCR values above 99.5% with UACI close to theoretical ideals. The ciphertext images exhibit uniform statistical distributions, a large key space, and accurate reversibility. These results confirm the method’s robustness against statistical and differential attacks, making it a secure and practical solution for medical image protection.

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Publication Details

Published
2025-07-11
DOI
https://doi.org/10.1109/cisat66811.2025.11181691
Primary Topic
Chaos-based Image/Signal Encryption
Type
article
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article

Medical image encryption based on four-dimensional chaotic system and DNA coding

Wei Ge, Yiqun Zhu
Chaos-based Image/Signal Encryption
article

Medical image encryption based on four-dimensional chaotic system and DNA coding

Wei Ge, Yiqun Zhu
article en

Abstract

To address the security challenges of medical images during network transmission and remote storage, this paper proposes a high-security image encryption algorithm that combines a four-dimensional Lorenz hyperchaotic system with DNA coding. The proposed method first utilizes a SHA-256 hash of the plaintext image to generate sensitive initial conditions, which are then used to drive the 4D Lorenz system to produce chaotic sequences. A Zigzag scan is employed to perform pixel-level permutation, followed by dynamic DNA encoding rules guided by the chaotic system. A DNA-XNOR diffusion process and cascading bit-level diffusion are introduced to enhance nonlinear confusion and global diffusion. Experimental results on various medical images demonstrate that the proposed algorithm achieves high information entropy, significantly reduces pixel correlation, and reaches NPCR values above 99.5% with UACI close to theoretical ideals. The ciphertext images exhibit uniform statistical distributions, a large key space, and accurate reversibility. These results confirm the method’s robustness against statistical and differential attacks, making it a secure and practical solution for medical image protection.

Shanghai Dianji University (CN)
Openalex Percentile: Top 73%
Chaos-based Image/Signal Encryption
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