Blockchains rely on economic incentives to ensure secure and decentralised operation, making incentive compatibility a core design concern. However, protocols are rarely deployed in isolation. Applications interact with the underlying consensus and network layers, and multiple protocols may run concurrently on the same chain. These interactions give rise to complex incentive dynamics that traditional, isolated analyses often fail to capture. We propose the first compositional game-theoretic framework for blockchain protocols. Our model represents blockchain protocols as interacting games across the application, network, and consensus layers. It enables formal reasoning about incentive compatibility under composition by introducing two key abstractions: the cross-layer game, which models how strategies in one layer influence others, and cross-application composition, which captures how application protocols interact concurrently through shared infrastructure. We illustrate our framework through case studies on Hashed Timelock Contracts (HTLCs), Layer-2 protocols, and Maximal Extractable Value (MEV) showing how compositional analysis reveals new subtle incentive vulnerabilities and supports modular security proofs. Also, by introduction of a novel rational miner model, we derive new conditions for the robustness of timelocks to bribing attacks.

翻译：区块链依赖经济激励来确保安全与去中心化运行，这使得激励相容性成为核心设计考量。然而，协议很少在隔离环境中部署。应用与底层共识层及网络层交互，多个协议可能在同一条链上并发运行。这些相互作用导致复杂的激励动态，而传统的孤立分析往往难以捕捉。我们提出首个面向区块链协议的可组合博弈论框架。该模型将区块链协议建模为横跨应用层、网络层和共识层的博弈交互。它通过引入两个关键抽象：跨层博弈（建模某一层策略如何影响其他层）以及跨应用组合（捕捉应用协议通过共享基础设施的并发交互方式），实现了对组合下激励相容性的形式化推理。我们通过哈希时间锁合约（HTLCs）、第二层协议以及最大可提取价值（MEV）的案例研究展示该框架，揭示组合分析如何发现新的微妙激励漏洞，并支持模块化安全证明。此外，通过引入一种新颖的理性矿工模型，我们推导出时间锁对抗贿赂攻击的鲁棒性新条件。