A Unified Framework for Generating 4-D Discrete Memristive Hyperchaotic Maps With Complex Dynamics and Application to Encryption
Why this work is in the frame
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Bibliographic record
Abstract
Traditional low dimensional chaotic maps suffer from limited dynamical complexity and weak randomness, reducing their effectiveness in applications. This paper presents a general framework for constructing 4-D memristive hyperchaotic maps, from which four representative hyperchaotic maps are developed. These maps exhibit diverse dynamical behaviors. Importantly, all four maps are designed without fixed points due to the inclusion of two oscillatory terms. By adjusting the internal memristor state, they generate infinitely many coexisting attractors, and they further enable controllable amplitude modulation as well as parameters driven attractors offset boosting. A digital hardware platform is developed to implement the proposed maps and experimental results demonstrate their robustness and feasibility in embedded environments. An image encryption algorithm based on it is designed, results exhibiting robust resistance against brute-force attacks, diverse noise attacks at varying intensities, cropping attacks and differential cryptanalysis.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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