Image encryption method based on small-world coupled mapping lattice and entropy extraction of cellular automata
Why this work is in the frame
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Bibliographic record
Abstract
This paper proposes an image encryption algorithm based on small-world coupled mapping lattice and cellular automata. First, the initial parameters are jointly derived using the key and plaintext to drive the CML to evolve under the red–black update, and the key stream and mask are adaptively generated by ECA and local entropy. Reversible mixing is achieved through scrambling and channel integer shearing + modulo 1 expansion. Subsequently, deterministic CFB diffusion and byte-level DNA substitution are performed to obtain the ciphertext. Decryption is precisely restored in the reverse process. Experiments on standard images show that this method achieves nearly uniform histograms, high pixel entropy, strong key sensitivity, and can resist common attacks such as noise and cropping. This framework is user-friendly, easy to parallelize and has strict security attributes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.005 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it