Vwe2psTS: Supporting Oracle-Based Conditional Payments from Joint Addresses
Bibliographic record
Abstract
Oracle-based Conditional (ObC) payments are widely used in real-world applications. They involve two mutually distrustful parties who wish to execute a payment contingent on the outcome of a real-world event. The payment succeeds only when the outcome is attested by a semi-honest oracle or a threshold number of oracles. The recently proposed VweTS [NDSS’23] significantly advances ObC payments as an underlying cryptographic primitive. However, VweTS supports only ObC payments from 2-of-2 multi-signature addresses, where spending requires two independent signatures, and does not accommodate joint addresses, where spending requires a joint signature. Payments made on blockchains requiring two independent signatures not only increase on-chain costs (e.g., transaction fees) but are also more vulnerable to discriminatory censorship compared to single-signature authentication. To overcome these limitations, we introduce a new cryptographic primitive: verifiable witness encryption of two-party signatures based on threshold signatures (Vwe2psTS). Vwe2psTS enables ObC payments from joint addresses on blockchains, thereby reducing on-chain costs while preserving security. We formally define the security of Vwe2psTS and present concrete constructions based on adaptor and BLS signatures for payment authentication. We prove the security of these constructions and evaluate Vwe2psTS’s performance relative to VweTS. Our results show that Vwe2psTS achieves superior performance in running time (when the number of oracles exceeds 3) and communication cost, though it incurs higher storage cost.
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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 | 0.003 | 0.009 |
| 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 | 0.002 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".