Health Insurance Portability and Accountability Act (HIPPA) Compliant Access Control Model for Web Services
Bibliographic record
Abstract
Health Insurance Portability and Accountability Act of 1996 (HIPAA) is a set of rules to be followed by health plans, doctors, hospitals, and other healthcare providers in the U.S. HIPAA privacy rules create national standards to protect individuals’ health information. Recently, there have been increasing demands and discussions about Web services-based healthcare applications. It is, therefore, necessary for HIPAA privacy rules to be standardized in Web services. However, so far no comprehensive solutions to the various privacy issues have been defined in this area. This paper summarizes the HIPAA privacy rules and surveys the topic of protecting health data privacy under the HIPAA. We propose a vocabulary-based Web services privacy framework with Role-based Access Control (RBAC) with privacy extensions and argue the HIPAA compliance for such framework. For illustration, we present the first two HIPAA rules in the extended RBAC model and embed into the HIPAA-compliant technical architecture for implementation of Web services.
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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 | 0.014 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".