Asynchronous Distributed Private-Key Generators for Identity-Based Cryptography
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
An identity-based encryption (IBE) scheme can greatly reduce the complexity of sending encrypted messages over the Internet. However, an IBE scheme necessarily requires a private-key generator (PKG), which can create private keys for clients, and so can passively eavesdrop on all encrypted communications. Although a distributed PKG has been suggested as a way to mitigate this problem for Boneh and Franklin’s IBE scheme, the security of this distributed protocol has not been proven and the proposed solution does not work over the asynchronous Internet. Further, a distributed PKG has not been considered for any other IBE scheme. In this paper, we design distributed PKG setup and private key extraction protocols in an asynchronous communication model for three important IBE schemes; namely, Boneh and Franklin’s IBE, Sakai and Kasahara’s IBE, and Boneh and Boyen’s BB1-IBE. We give special attention to the applicability of our protocols to all possible types of bilinear pairings and prove their IND-ID-CCA security in the random oracle model. Finally, we also perform a comparative analysis of these protocols and present recommendations for their use. 1
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
| gpt | no category Domain: not available · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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