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<p>Chaotic maps are highly suitable for cryptographic applications because of their unpredictability, sensitivity to initial conditions, and control parameters. However, low-dimensional chaotic maps have simple structures but offer lower security, while high-dimensional chaotic maps provide higher security but are more complex to implement. To address these issues, we first introduce a three-dimensional coupled chaotic map (3D-CHAM) based on the Hénon map and the Arnold cat map. Using this newly designed chaotic map, we develop a Chaotic-map-based Hierarchical Dynamic Image Encryption (CHDIE) algorithm. This framework combines three-level permutation, pixel-value classification perception, dynamic DNA encryption, and post-processing diffusion to enhance security at multiple levels. Simulation experiments and security analyses demonstrate that, compared to traditional chaotic maps, 3D-CHAM exhibits stronger unpredictability, a larger key space, and a broader chaotic range. The CHDIE algorithm, built on the 3D-CHAM, achieves or surpasses the performance of leading chaotic encryption algorithms in sensitivity analysis (&gt; 99.6%), resistance to differential attacks (NPCR ≈ 99.60%, UACI ≈ 33.4%), information entropy (average 7.9992), and ciphertext pixel correlation (close to 0). This algorithm effectively resists various security threats, such as statistical analysis and differential attacks, and can encrypt different images into random ciphertexts, demonstrating excellent universality and security.</p>

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Dynamic RGB image encryption algorithm with pixel-value-driven partitioning and a newly designed three-dimensional chaotic map

  • 期刊论文

  • 发表日期：

    2026年2月3日

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  • Ru-Hui Shi,
  • Yu-Guang Yang,
  • Guang-Bao Xu,
  • Dong-Huan Jiang,
  • Dong-Hua Jiang

摘要

Chaotic maps are highly suitable for cryptographic applications because of their unpredictability, sensitivity to initial conditions, and control parameters. However, low-dimensional chaotic maps have simple structures but offer lower security, while high-dimensional chaotic maps provide higher security but are more complex to implement. To address these issues, we first introduce a three-dimensional coupled chaotic map (3D-CHAM) based on the Hénon map and the Arnold cat map. Using this newly designed chaotic map, we develop a Chaotic-map-based Hierarchical Dynamic Image Encryption (CHDIE) algorithm. This framework combines three-level permutation, pixel-value classification perception, dynamic DNA encryption, and post-processing diffusion to enhance security at multiple levels. Simulation experiments and security analyses demonstrate that, compared to traditional chaotic maps, 3D-CHAM exhibits stronger unpredictability, a larger key space, and a broader chaotic range. The CHDIE algorithm, built on the 3D-CHAM, achieves or surpasses the performance of leading chaotic encryption algorithms in sensitivity analysis (> 99.6%), resistance to differential attacks (NPCR ≈ 99.60%, UACI ≈ 33.4%), information entropy (average 7.9992), and ciphertext pixel correlation (close to 0). This algorithm effectively resists various security threats, such as statistical analysis and differential attacks, and can encrypt different images into random ciphertexts, demonstrating excellent universality and security.