A Lightweight Mutual Authentication Scheme with Fault Tolerance in Smart Elderly Care 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
Smart elderly care system, which integrates IoT technologies into traditional healthcare system, has recently received considerable attention, as it can significantly alleviate pension and medical problems in an aging society. As the first shield to address security issues in the IoT environment, authentication, especially mutual authentication, has played a critical role. However, none of the existing authentication schemes can simultaneously achieve fault tolerance, privacy preservation, and efficiency. In this paper, we propose a lightweight mutual authentication scheme that can simultaneously support the aforementioned three properties. In particular, we integrate the novel XOR filter and Hamming distance to make fault tolerance and privacy preservation possible. By employing efficient Rabin public key encryption, we design our lightweight authentication scheme, which only involves two rounds of communication. Detailed security analysis demonstrates that our scheme is secure and privacy-preserving, and the extensive evaluation results also validate its efficiency.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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