Prrr: Personal Random Rewards for Blockchain Reporting

2025-11-16

AI Summary

Report publication protocols in smart contracts face a fundamental trade-off between security and performance—centralization arises when relying on few trusted publishers, while open publication incurs excessive on-chain redundancy. Method: This paper proposes an incentive-compatible blockchain mechanism that rewards timely reporting. Its core innovation is the first “ex-ante synthetic asymmetry” mechanism design paradigm, which introduces deliberate strategic asymmetry among participants via personalized stochastic rewards and second-price auction–style settlement—departing from conventional symmetric reward schemes. Contribution/Results: Under subgame-perfect Nash equilibrium analysis, the mechanism provably resists collusion and Sybil attacks. Experimental evaluation demonstrates substantial reduction in on-chain report redundancy, improved system efficiency, and enhanced decentralization and security. The mechanism thus provides a scalable, attack-resilient reporting infrastructure for time-sensitive smart contracts.

Technology Category

• Multiagent Systems: Mechanism Design
• Game Theory and Economic Paradigms: Mechanism Design
• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust

Application Category

• Security and Privacy: Cryptocurrency and smart contracts
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

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.

Problem

• Incentivizing timely blockchain reporting with security
• Overcoming centralization risks versus excessive report trade-offs
• Introducing asymmetric rewards for game-theoretic mechanism design

Innovation

• Personal Random Rewards with heterogeneous values
• Ex-Ante Synthetic Asymmetry mechanism design
• Second-price settlement ensuring incentive compatibility