BACKWARDS COMPATIBLE, MULTI-LEVEL REGIONS-OF-INTEREST (ROI) IMAGE ENCRYPTION ARCHITECTURE WITH BIOMETRIC AUTHENTICATION
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
Digital image archival and distribution systems are an indispensable part of the modern digital age. Organizations perceive a need for increased information security. However, conventional image encryption methods are not versatile enough to meet more advanced image security demands. We propose a universal multi-level ROI image encryption architecture that is based on biometric data. The proposed architecture ensures that different users can only view certain parts of an image based on their level of authority. Biometric authentication is used to ensure that only an authorized individual can view the encrypted image content. The architecture is designed such that it can be applied to any existing raster image format while maintaining full backwards compatibility so that images can be viewed using popular image viewers. Experimental results demonstrate the effectiveness of this architecture in providing conditional content access.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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