EHKEA: A Lightweight and Secure Authentication Protocol for Healthcare Iot Systems in 5G Networks with Enhanced Resistance to Emerging Threats
Why this work is in the frame
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Bibliographic record
Abstract
Secure authentication remains a critical challenge in healthcare IoT (H-IoT) systems, where constrained devices must ensure data integrity, privacy, and resilience despite limited resources. This paper proposes EHKEA, a lightweight mutual authentication and key establishment protocol designed specifically for H-IoT environments. EHKEA relies solely on symmetric cryptographic primitives and ephemeral randomness to provide mutual authentication, forward secrecy and resistance to common attacks such as replay, impersonation, and man-in-the-middle intrusions. We formally verify EHKEA in the Tamarin prover under the Dolev-Yao adversary model, proving key security properties including injective agreement and session key secrecy. A detailed informal analysis further confirms its robustness against desynchronization, insider threats, and key compromise impersonation. Comparative analysis with recent H-IoT protocols demonstrates that EHKEA achieves superior efficiency while offering stronger security guarantees, making it well-suited for deployment in real-time healthcare monitoring applications.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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