Image Encryption via Data-Identified Discrete Chaotic Maps

Computer Science > Cryptography and Security [Submitted on 20 May 2026] Image Encryption via Data-Identified Discrete Chaotic Maps Wenyuan Lia, Xiao-Yun Wang, Zhigang Zhu, Xiaofeng Zhang, Li Zhang In this work, we propose a data-driven image encryption framework that identifies chaotic maps directly from data using the SINDy-PI algorithm. Unlike conventional encryption schemes relying on predefined maps, our method learns the full explicit dynamics -- including cross-terms and higher-order nonlinearities -- from observational data. The validity of this approach is verified on three distinct chaotic systems: the H{é}non map, the three-dimensional logistic map, and the piecewise-linear Lozi map, demonstrating its generality. The encryption key consists solely of initial conditions; the map structure itself becomes data-dependent, introducing an extra layer of security. Moreover, even when the initial conditions are fixed, different training data (e.g., with a tiny noise seed) lead to slightly different maps, which produce completely different ciphertexts (NPCR \approx 99.6\%, UACI \approx 33.5\%). Numerical experiments on the H{é}non system show near-ideal information entropy (\approx 8 bits), negligible inter-pixel correlation, and extreme sensitivity to initial conditions: a perturbation of 10^{-16} causes total decryption failure. The scheme resists both differential and statistical attacks, with NPCR and UACI values matching theoretical ideals. Our results establish a new paradigm for chaos-based cryptography beyond fixed maps. Comments: 16 pages, 6 figures Subjects: Cryptography and Security (cs.CR) Cite as: arXiv:2605.21118 [cs.CR]   (or arXiv:2605.21118v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2605.21118 Focus to learn more Submission history From: Xiao-Yun Wang [view email] [v1] Wed, 20 May 2026 12:49:17 UTC (590 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-05 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)