Color Image Encryption by Using Modified E0 Keystream Generator with Peter De Jong Chaotic Map
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In light of the current developments and the widespread use of the Internet and the sensitive data contained in images, it was necessary to develop new methods to protect data during its transmission.This paper will modify the E0 algorithm key generator by adding two additional records to the original generator to become 6, integrating them with dice to determine the choice of the bit resulting from the key, which increases the complexity and randomness of the generated key, additionally, included Peter De Jong's chaotic map features with image encryption procedure.The proposed method yielded promising results, as demonstrated by the NIST randomness test, confirming the generated key's randomness.Furthermore, the entropy values were close to the ideal value of 8, and correlation coefficients gives a good result close to 1, since all PSNR values are low, about 9.95dB the quality of the image encoding is good.In contrast to MSE around10128.22,all numbers are very high, indicating that the encoded image is very different from the original image.while the NPCR and UACI tests achieved about 99.60% and 33.50%, respectively.Other standard evaluations also confirmed that the proposed approach is robust against brute force attacks.
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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 | 0.000 | 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 | 0.000 | 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