Smart contracts, the stateful programs running on blockchains, often rely on reports. Publishers are paid to publish these reports on the blockchain. Designing protocols that incentivize timely reporting is the prevalent reporting problem. But existing solutions face a security-performance trade-off: Relying on a small set of trusted publishers introduces centralization risks, while allowing open publication results in an excessive number of reports on the blockchain. We identify the root cause of this trade-off to be the standard symmetric reward design, which treats all reports equally. We prove that no symmetric-reward mechanism can overcome the trade-off. We present Personal Random Rewards for Reporting (Prrr), a protocol that assigns random heterogeneous values to reports. We call this novel mechanism-design concept Ex-Ante Synthetic Asymmetry. To the best of our knowledge, Prrr is the first game-theoretic mechanism (in any context) that deliberately forms participant asymmetry. Prrr employs a second-price-style settlement to allocate rewards, ensuring incentive compatibility and achieving both security and efficiency. Following the protocol constitutes a Subgame-Perfect Nash Equilibrium, robust against collusion and Sybil attacks. Prrr is applicable to numerous smart contracts that rely on timely reports.

翻译：智能合约作为运行在区块链上的有状态程序，通常依赖外部报告。发布者通过将报告上链获得报酬。设计激励及时报告的协议是报告问题中的核心挑战，但现有方案面临安全性与性能的权衡：依赖少数可信发布者会引入中心化风险，而允许开放发布则导致链上报告数量过多。我们指出这一权衡的根本原因在于标准的对称奖励设计——对所有报告一视同仁。我们证明任何对称奖励机制都无法突破此权衡。为此提出"报告机制的个性化随机奖励"（Prrr），这是一种为报告分配随机异质值的协议。我们称这一新颖的机制设计概念为"事前合成非对称性"。据我们所知，Prrr是首个（在任何语境下）有意识地构造参与者非对称性的博弈论机制。Prrr采用第二价格式结算分配奖励，确保激励相容性并同时实现安全性与效率。遵循该协议构成子博弈完美纳什均衡，能够抵抗合谋攻击与女巫攻击。Prrr适用于众多依赖及时报告的智能合约。