Incentive Mechanism Design for Privacy-Preserving Decentralized Blockchain Relayers
🤖 AI Summary
This work addresses the privacy risks inherent in public blockchains, where transaction transparency can lead to user identity leakage, and highlights the limitations of relying on a single relay node, which introduces a single point of failure and undermines privacy. To overcome these challenges, the paper proposes a decentralized relay architecture that, for the first time, integrates evolutionary game theory into blockchain relay systems. By modeling non-cooperative interactions among relays, a probabilistic upload mechanism is designed to jointly optimize privacy and reliability under a mixed-strategy Nash equilibrium. Theoretical analysis demonstrates that this strategy constitutes the unique evolutionarily stable equilibrium and reveals fundamental trade-offs among privacy, reliability, robustness, and operational cost. Extensive simulations confirm the mechanism’s stability and practicality, showing that system outage probability remains below 0.05 even under high transaction costs and various parameter perturbations.
Application Category
📝 Abstract
Public blockchains, though renowned for their transparency and immutability, suffer from significant privacy concerns. Network-level analysis and long-term observation of publicly available transactions can often be used to infer user identities. To mitigate this, several blockchain applications rely on relayers, which serve as intermediary nodes between users and smart contracts deployed on the blockchain. However, dependence on a single relayer not only creates a single point of failure but also introduces exploitable vulnerabilities that weaken the system's privacy guarantees. This paper proposes a decentralized relayer architecture that enhances privacy and reliability through game-theoretic incentive design. We model the interaction among relayers as a non-cooperative game and design an incentive mechanism in which probabilistic uploading emerges as a unique mixed Nash equilibrium. Using evolutionary game analysis, we demonstrate the equilibrium's stability against perturbations and coordinated deviations. Through numerical evaluations, we analyze how equilibrium strategies and system behavior evolve with key parameters such as the number of relayers, upload costs, rewards, and penalties. In particular, we show that even with high transaction costs, the system maintains reliability with an outage probability below 0.05 . Furthermore, our results highlight a fundamental trade-off between privacy, reliability, robustness, and cost in decentralized relayer systems.
Problem
Research questions and friction points this paper is trying to address.
privacy
blockchain relayers
decentralization
single point of failure
incentive mechanism
Innovation
Methods, ideas, or system contributions that make the work stand out.
decentralized relayers
incentive mechanism design
game-theoretic privacy
mixed Nash equilibrium
evolutionary game analysis
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