Health Insurance Portability and Accountability Act (HIPPA) Compliant Access Control Model for Web Services
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
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.
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 | 0.002 | 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 | 0.001 | 0.007 |
| Open science | 0.000 | 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