Confidential blockchains leveraging Trusted Execution Environments (TEEs) have garnered extensive attention for transaction confidentiality. In this paper, we first taxonomize two classes of attacks against confidential blockchains, i.e., execution-inference and execution-replay attacks, which exploit TEEs' long-lasting side-channel and state-continuity issues to compromise the confidentiality of existing consortium blockchains. Then, we present ODYSSEY, a confidential blockchain that efficiently mitigates these attacks. The core innovations of ODYSSEY are the following: (1) Its delegation model: clients delegate transaction execution to their designated trustees, while other participants synchronize only the execution results, which significantly reduces the attack surface while preserving confidentiality and system performance. (2) Two novel techniques to improve ODYSSEY's efficiency and security: location-aware concurrent execution and delegation failure handler. Finally, we develop a prototype of ODYSSEY on FISCO BCOS, an enterprise-grade consortium blockchain platform. We have conducted various experiments, and our evaluation results show that in a WAN environment with 3 nodes, ODYSSEY can achieve about 4k throughput while keeping latency as low as 0.4-0.5s.

翻译：利用可信执行环境（TEE）的机密区块链在交易保密方面引起了广泛关注。本文首先分类了针对机密区块链的两类攻击，即执行推断攻击和执行重放攻击，这些攻击利用TEE的持久侧信道与状态持续性问题，破坏了现有联盟链的机密性。随后，我们提出ODYSSEY——一种高效缓解这些攻击的机密区块链。其核心创新如下：(1) 委托模型：客户端将交易执行委托给指定的受托人，其他参与者仅同步执行结果，从而在保持机密性与系统性能的同时显著减小攻击面。(2) 提升ODYSSEY效率与安全性的两项新技术：位置感知并发执行与委托失败处理机制。最后，我们在企业级联盟链平台FISCO BCOS上开发了ODYSSEY原型。通过多项实验，评估结果表明：在包含3个节点的广域网环境中，ODYSSEY可在维持0.4-0.5秒低延迟的同时达到约4000吞吐量。