ReplayMPC: A Fast Failure Recovery Protocol for Secure Multiparty Computation Applications using Blockchain
ReplayMPC: A Fast Failure Recovery Protocol for Secure Multiparty Computation Applications using Blockchain
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DOI：
10.1109/smartcomp58114.2023.00033
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发表时间：
2023-06
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通讯作者：
Oscar G. Bautista;Kemal Akkaya;Soamar Homsi
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文献类型：
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作者：
Oscar G. Bautista;Kemal Akkaya;Soamar Homsi
尽管最近安全多方计算 (SMPC) 的性能改进使其成为隐私保护机器学习 (ML) 等复杂应用的实用解决方案，但鲁棒性等其他特性对其实际可行性也至关重要。例如，由于 SMPC 下的 ML 训练可能需要更长的时间（例如，在许多情况下需要数小时或数天），任何计算中断都将需要重新启动进程，这会导致更多的延迟和计算资源的浪费。虽然可以在单独的数据库中维护交换的 SMPC 消息，但应保证其完整性和真实性以便以后能够重新使用它们。因此，在本文中，我们提出了 ReplayMPC，一种基于区块链技术的 SMPC 高效故障恢复机制，能够在任何类型的通信或系统故障后恢复和重新同步 SMPC 各方。我们的方法允许 SMPC 各方保存他们在恢复期间用作恢复点的计算状态快照，然后通过从存储在区块链上的不可变消息中检索信息来重现最后的计算轮次。我们在 Algorand 区块链上的实验结果表明，恢复比从头开始整个过程要快得多，节省了时间、计算和网络资源。
Although recent performance improvements to Secure Multiparty Computation (SMPC) made it a practical solution for complex applications such as privacy-preserving machine learning (ML), other characteristics such as robustness are also critical for its practical viability. For instance, since ML training under SMPC may take longer times (e.g., hours or days in many cases), any interruption of the computation will require restarting the process, which results in more delays and waste of computing resources. While one can maintain exchanged SMPC messages in a separate database, their integrity and authenticity should be guaranteed to be able to re-use them later. Therefore, in this paper, we propose ReplayMPC, an efficient failure recovery mechanism for SMPC based on blockchain technology that enables resuming and re-synchronizing SMPC parties after any type of communication or system failures. Our approach allows SMPC parties to save computation state snapshots they use as restoration points during the recovery and then reproduce the last computation rounds by retrieving information from immutable messages stored on a blockchain. Our experiment results on Algorand blockchain show that recovery is much faster than starting the whole process from scratch, saving time, computation, and networking resources.