UACML: Unified Access Control Modeling Language
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
Incorporating security requirements into system design models is receiving increasing interest. Access control requirements are an important part of overall system security requirements. Existing approaches that incorporate access control requirements into system design models have directly been developed on top of specific access control models. In these approaches, there exists a tight-coupling between the modeling language and underlying access control model(s) on which the modeling language is developed. Consequently, these approaches can only support security requirements for the access control model(s) on which they were developed. We propose an alternative approach in this work by adopting a "metamodel of access control" as a basis for developing a UML-based modeling language. The usage of a metamodel of access control offers at least two benefits: (i) our modeling language is able to represent a variety of access control requirements in a generic way and (ii) our modeling language is independent of specific access control models. By using examples, we demonstrate that our approach is useful for developing a generic modeling language of access control that is simple, yet powerful for representing a variety of access control models.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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