A secure mobile healthcare system using trust-based multicast scheme
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
Due to the introduction of telecommunication technologies in telemedicine services, the expeditious development of wireless and mobile networks has stimulated wide applications of mobile electronic healthcare systems. However, security is an essential system requirement since many patients have privacy concerns when it comes to releasing their personal information over the open wireless channels. For this reason, this study discusses the characteristics and security issues with wireless and pervasive data communications for a ubiquitous and mobile healthcare system which consists of a number of mobile devices and sensors attached to a patient. These devices form a mobile ad hoc sensor network and collect data that are sent to a hospital or healthcare center for monitoring. Subsequently, this paper discusses the innovation and design of a novel trust evaluation model. We then propose a secure multicast strategy that employs trust in order to evaluate the behavior of each node, so that only trustworthy nodes are allowed to participate in communications, while the misbehavior of malicious nodes is effectively prevented. We analyze the security properties of our multicast scheme and evaluate its performance based on simulation experiments. Our experimental results demonstrate that our scheme not only achieves the necessary data transmission in mobile environments, but also provides more security with reasonably little additional overhead.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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