Blind RSA signatures from the <inline-formula><tex-math id="M1">$ t- $</tex-math></inline-formula>generalized Lehmer sequences of some classes of groups
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Bibliographic record
Abstract
In this paper, we introduce the $ t- $generalized Lehmer sequences. We also define these sequences in finite groups and study the period for some special groups. The algebraic properties are analyzed in the finite groups $ G_m $ and $ H_{(m, s, k)} $. Two blind RSA signature schemes are designed that leverage the periodicity and unpredictability of these sequences. The proposed approach achieves correctness, unforgeability under chosen-message attacks, and blindness, with security grounded in the RSA assumption and sequence unpredictability. Compared with existing RSA-based blind signatures, the proposed method reduces reliance on random number generators while providing comparable efficiency. These features make it particularly attractive in constrained or adversarial environments such as IoT devices or weak entropy settings. The proposed approach introduces new directions for recurrence-based sequences in constructing blind RSA signatures and provides a new application of sequences in groups for cryptography.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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