Development of image encryption method using surjective finite automata and custom S-box within the advanced encryption standard framework

Authors

DOI:

https://doi.org/10.15587/1729-4061.2025.348368

Keywords:

image encryption, surjective finite automaton, custom S-box, AES

Abstract

The object of the study is the AES-128 (Advanced Encryption Standard) – based image-encryption scheme. The problem solved is the persistence of residual image structure and sub-ideal statistical security when classical AES is naively applied to visual data. The generated cipher images yield near-maximal entropy with low pixel correlations and uniform histograms. Encrypted-image Chi-square values concentrate around 200–310 (close to a uniform distribution), the NPCR (Number Of Changing Pixel Rate) consistently 99.623–99.657% with a best case 99.6547%, and the UACI (Unified Averaged Changed Intensity) ≈ 33.64% per channel (RGB combined ≈ 22%). Robustness tests show ≈ 30.7 dB at 50% cropping and ≈ 39.5–39.7 dB at 0.01 salt-and-pepper noise and 6.25% cropping. These outcomes are explained by the bit-level, state-dependent permutations introduced by the surjective automaton (boosting diffusion) and by the nonlinear S-box synthesized under strict criteria (e. g., bounded differential uniformity, high nonlinearity) that heighten confusion, and operation in CBC (Cipher Block Chaining) mode supplies semantic security. Other unique features that facilitate the solution are the substituting of ShiftRows/MixColumns with surjective finite automata; a custom, criteria-optimized S-box; and a 10-round AES-128 CBC pipeline with a random. Taking all of this together yielding observed statistical uniformity, a high NPCR/UACI, and stable robustness under degradation. Lastly, the findings demonstrate the applicability to secure multimedia transmission and storage in channels prone to noise or partial data loss, and being data-agnostic, that the transformations can generalize to text and generic binary data when carefully managed

Author Biographies

Alibek Barlybayev, L.N. Gumilyov Eurasian National University

Doctor PhD, Professor

Department of Artificial Intelligence Technologies

Zhanat Saukhanova, L.N. Gumilyov Eurasian National University

Candidate of Physical and Mathematical Sciences, Associate Professor

Department of Information Security

Gulmira Shakhmetova, L.N. Gumilyov Eurasian National University

Senior Lecturer

Department of Information Security

Altynbek Sharipbay, L.N. Gumilyov Eurasian National University

Doctor of Technical Sciences, Professor

Department of Artificial Intelligence Technologies

Sayat Raykul, L.N. Gumilyov Eurasian National University

Student

Department of Information Security

Altay Khassenov, L.N. Gumilyov Eurasian National University

Student

Department of Information Security

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Development of image encryption method using surjective finite automata and custom S-box within the advanced encryption standard framework

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Published

2025-12-30

How to Cite

Barlybayev, A., Saukhanova, Z., Shakhmetova, G., Sharipbay, A., Raykul, S., & Khassenov, A. (2025). Development of image encryption method using surjective finite automata and custom S-box within the advanced encryption standard framework. Eastern-European Journal of Enterprise Technologies, 6(9 (138), 77–99. https://doi.org/10.15587/1729-4061.2025.348368

Issue

Vol. 6 No. 9 (138) (2025): Information and controlling system

Section

Information and controlling system

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Copyright (c) 2025 Alibek Barlybayev, Zhanat Saukhanova, Gulmira Shakhmetova, Altynbek Sharipbay, Sayat Raykul, Altay Khassenov

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