Color Image Encryption Based on 3D-SBFCM with Dynamic Rectangular Partitioning and Dynamic S-Box Substitution
Ting Wang, Xiaoyan Yang, Bin Ge, Chenxing Xia, Houyue Wu · Entropy · 2026
Existing chaos-based color image encryption algorithms still face several challenges, including insufficient dynamical complexity of low-dimensional chaotic maps, residual boundary regularity caused by fixed block partitioning, and limited diffusion among RGB channels. To address these issues, this paper proposes a color image encryption algorithm based on a three-dimensional sine-bilinear fully coupled chaotic map (3D-SBFCM). The proposed map integrates sinusoidal modulation, linear coupling, and bilinear cross-coupling within a mod-1 mapping framework, thereby improving the complexity and pseudorandomness of the generated chaotic sequences. In addition, a residual-feasibility-constrained dynamic rectangular partitioning mechanism is developed to generate reversible non-uniform image blocks and reduce the structural regularity associated with fixed-size partitioning. Based on this partitioning structure, inter-block permutation among same-size blocks and intra-block two-dimensional permutation are performed to weaken both global and local spatial correlations. Plaintext-related initialization, dynamic S-box substitution, and forward-backward cross-channel diffusion are further incorporated into the overall permutation-diffusion framework to enhance plaintext sensitivity, nonlinear confusion, and perturbation propagation across RGB channels. Experimental results demonstrate that the proposed algorithm effectively conceals the statistical characteristics of plaintext images, with information entropy values higher than 7.999 for all color channels and NPCR/UACI values close to their theoretical expectations. The algorithm also shows satisfactory robustness against cropping and noise attacks. These results indicate that the proposed method provides an effective and secure solution for color image encryption.