Information Flow Analysis in Role-Based Security Systems
Bibliographic record
Abstract
This paper examines the application of information flow analysis to rolebased protection systems. Starting with basic information flow axioms and a security policy, we propose a means of ensuring that a given role-based scheme is consistent with the specified security policy. The proposed method uses graph theory and, in particular, treats this problem as an instance of subgraph isomorphism to determine the consistency of a role-based scheme with a given security policy. Keywords: Security policy, information flow, role, role-based protection, subgraph isomorphism. 1 Introduction Role-based security is a flexible means of managing large numbers of access rights. A role is a named collection of privileges [2, 14, 21] where a privilege is a unit of access to system information. User-role authorization grants the user access to the privileges defined in the role. 1 This work was supported in part by a grant from the Natural Science & Engineering Research Council of Canada. 1369 Rol...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.003 | 0.009 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".