Evidence map›Paper›PMID 42352168›Full record

ArticleEntropy (Basel, Switzerland)2026

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

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Ting WangSchool of Information Engineering, Huainan Union University, Huainan 232038, China.ORCID 0000-0002-4375-8052
Xiaoyan YangSchool of Information Engineering, Huainan Union University, Huainan 232038, China.
Bin GeSchool of Computer Science and Engineering, Anhui University of Science and Technology, Huainan 232001, China.
Chenxing XiaSchool of Computer Science and Engineering, Anhui University of Science and Technology, Huainan 232001, China.
Houyue WuSchool of Computer and Information Engineering, Bengbu University, No. 1866 Caoshan Road, Bengbu 233030, China.ORCID 0000-0002-6881-9579

Funding

Anhui Province New Era Education Quality Project (Graduate Education) Overseas Training 2024dshwyx019Anhui Province Young Key Teachers Overseas Study and Research Funding Project JWFX2023016Bengbu University 2024 General Program of University Research 2024ZR02National Natural Science Foundation of China 62102003Natural Science Foundation of Anhui Province 2508085MF167Open Fund of State Key Laboratory of Digital Intelligent Technology for Unmanned Coal Mining SZQZ2025-2-003the Model Virtual Simulation Training Center for Information Security 2024sfxf013the Scientific Research Project of Higher Education Institutions of Anhui Province (Natural Science) 2024AH051713
6 · The paper itself

Abstract

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.

Indexed as

chaotic mapcolor image encryptioncross-channel diffusiondynamic S-boxhierarchical scrambling

Identifiers

PMID42352168
PMCPMC13298940

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.