Rational Secret Sharing with and without Synchronous Broadcast, Conspicuous Secrets, Malicious Players and Unbounded Opponents
Bibliographic record
Abstract
In secret sharing we are asked to split a secret into several shares in such a way that a minimum number of shares is necessary and sufficient to reconstruct the secret. Rational secret sharing considers secret sharing in the context of adversarial players who want to learn the secret but, secondarily, want to prevent other players from learning the secret. \n\nWe present protocols, and bounds on the effectiveness of any protocol, for recombining secret shares in the presence of players who do not want others to learn the secret (rationality), may not want to learn the secret themselves (maliciousness), may be colluding, may have unbounded computational capacity, may be able to synchronize sends (asynchronous/synchronous broadcast), and/or may be able to recognize the secret independently (conspicuousness).\n\nWe propose four protocols and analyze their security against players and coalitions who are each rational or malicious. We also prove three results that show protocols using only asynchronous broadcast are less secure than what can be achieved by protocols using synchronous broadcast.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".