BAB-SDMM: Blockchain Attribute Based Secure Data Management Model
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
The secure access and reliable access revocation methods of modern digital systems are based on access control mechanisms.Access policies, which are used in access control mechanisms, are very important in safeguarding security and ensuring data protection.It is evident that the protection and tamper-proofing of such policies are very important.In addition, efficient access revocation schemes are required to promptly remove access privileges when users are no longer needed or authorized.The shortcomings of existing systems in ensuring efficient, streamlined access revocation and tamper-proof protection of access control policies underscore the need for innovative solutions.In this paper, we have introduced the novel Blockchain Attribute-Based Secure Data Management Model (BAB-SDMM).Our model is the first to integrate attribute-based encryption (ABE), Attribute-Based Access Control (ABAC), and blockchain to achieve multiple security features as well as provide partial and complete revocation at the same time.The experimental results and analysis, performed using the Ethereum blockchain network, demonstrated the enhanced performance of the proposed BAB-SDMM compared to existing research works.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.002 | 0.001 |
| 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