HB <sup>đ</sup> entity authentication for low-cost pervasive devices
Why this work is in the frame
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Bibliographic record
Abstract
The HB-like entity authentication protocols for low-cost pervasive devices have attracted a great deal of attention because of their simplicity, computational efficiency and solid security foundation on a well-studied hard problemâlearning parity with noise. By far, the most efficient protocol is HB#, which is provably resistant to the GRS attack under the conjecture that it is secure in the DET-model. However, in order to achieve 80-bit security, a typical HB# authentication key comprises over 1000 bits, which imposes considerable storage burdens on resource-constrained devices. In this study, the authors propose a new HB-like protocol: HBîą. The protocol makes use of a special type of circulant matrix, in contrast to the Toeplitz matrix in HB#, to significantly reduce storage consumption and overcome a subtle security proof inefficacy in HB#. In addition, the authors introduce a masking technique that substantially increases noise level from an adversary's standpoint, and thus improves protocol performance. The authors demonstrate that 613-bit authentication key suffices for 80-bit security in the HBîą protocol, which is quite competitive and more appealing for low-cost devices.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.013 |
| 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