An Efficient Multicast Authenticated Encryption Scheme for Smart Elderly Care Systems
Why this work is in the frame
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Bibliographic record
Abstract
Undoubtedly, smart elderly care systems can leverage Internet of Things (IoT) technology to enhance senior living services by integrating connected devices and sensors. Nevertheless, it is still a challenging issue to achieve secure and efficient multicast group communication among these IoT devices in smart elderly care systems, as IoT devices can dynamically become targets during multicast communication. To address this challenge, in this paper, we propose a new efficient multicast authenticated encryption scheme, which is characterized by integrating Merkle Tree, prefix encoding, XOR filters, and ASCON techniques to provide a robust solution for secure and personalized eldercare services in IoT-enabled environments. Security analysis demonstrates that our proposed scheme can satisfy the confidentiality and integrity requirements. In addition, the performance evaluation confirms that our proposed scheme is computationally efficient.
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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 | 0.000 | 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 | 0.000 | 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