Self-Sovereignty Identity Management Model for Smart Healthcare System
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
An identity management system is essential in any organisation to provide quality services to each authenticated user. The smart healthcare system should use reliable identity management to ensure timely service to authorised users. Traditional healthcare uses a paper-based identity system which is converted into centralised identity management in a smart healthcare system. Centralised identity management has security issues such as denial of service attacks, single-point failure, information breaches of patients, and many privacy issues. Decentralisedidentity management can be a robust solution to these security and privacy issues. We proposed a Self-Sovereign identity management system for the smart healthcare system (SSI-SHS), which manages the identity of each stakeholder, including medical devices or sensors, in a decentralisedmanner in the Internet of Medical Things (IoMT) Environment. The proposed system gives the user complete control of their data at each point. Further, we analysed the proposed identity management system against Allen and Cameron's identity management guidelines. We also present the performance analysis of SSI as compared to the state-of-the-art techniques.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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