Research on Chaotic Digital Image Encryption Based on ARM Platform
Why this work is in the frame
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Bibliographic record
Abstract
With the wide application of digital image processing technology in various fields, how to ensure the privacy and security of image data has become an urgent problem to be solved. To this end, this study selected the chaotic encryption algorithm, focusing on its encryption performance on the real low-light image dataset RENOIR on the ARM platform. After choosing a specific ARM hardware and software environment, a series of encryption experiments were performed using the RENOIR dataset. The experimental evaluation criteria include PSNR value of encrypted image, information entropy and encryption execution time on ARM platform. Preliminary results show that the chaotic encryption algorithm can effectively protect image content in this environment, has high randomness and unpredictability, and its execution efficiency meets the needs of practical applications.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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