ASTP: Agent-Based Secure and Trustworthy Packet-Forwarding Protocol for eHealth
Bibliographic record
Abstract
Security has been recognized as a key issue for the expansion of eHealth application, where highly sensitive patient's medical data are routed through a non-secure wireless network. In this paper, we look into the various security and privacy requirements for the eHealth application and propose an agent-based secure and trustworthy packet-forwarding Protocol (ASTP) considering the neighbor nodes previous and recent activities. ASTP incorporated with proper security tools that enhanced the overall performance of a cooperative multi-hop wireless network used for an eHealth application. The proposed protocol can successfully detects malicious nodes and the information is used and shared to the neighbors to avoid co-operating with them either for data forwarding, aggregation or any other cooperative function. Patient privacy is maintained by using an renewable pseudo-identity. Finally, security analysis and experimental results demonstrate that ASTP improves the average packet delivery ratio and maintains the require security and privacy at the cost of an acceptable communication delay.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".