ODYSSEY: Reestablishing Confidentiality in Confidential Blockchain via Delegated Execution

Abstract: 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.