DEVELOPMENT OF IMAGE ENCRYPTION METHOD USING SURJECTIVE FINITE AUTOMATA AND CUSTOM S-BOX WITHIN THE ADVANCED ENCRYPTION STANDARD FRAMEWORK

Barlybayev A. Saukhanova Z. Shakhmetova G. Sharipbay A. Raykul S. Khassenov A.
2025 Technology Center

Eastern-European Journal of Enterprise Technologies
2025 #6 Issue 9 77 - 99 pp.

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. Copyright

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

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Department of Artificial Intelligence Technologies, Kazakhstan
Department of Information Security, Kazakhstan
L.N. Gumilyov Eurasian National University, Satbaev str., 2, Astana, 010000, Kazakhstan

Department of Artificial Intelligence Technologies
Department of Information Security
L.N. Gumilyov Eurasian National University

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