ZEXE: Enabling Decentralized Private Computation

ZEXE: Enabling Decentralized Private Computation
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DOI:
10.1109/sp40000.2020.00050
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发表时间:
2020-05
期刊:
2020 IEEE Symposium on Security and Privacy (SP)
影响因子:
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通讯作者:
Sean Bowe;A. Chiesa;M. Green;Ian Miers;Pratyush Mishra;Howard Wu
Sean Bowe;A. Chiesa;M. Green;Ian Miers;Pratyush Mishra;Howard Wu
中科院分区:
其他
文献类型:
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作者:
Sean Bowe;A. Chiesa;M. Green;Ian Miers;Pratyush Mishra;Howard Wu

文献摘要

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支持丰富应用程序的基于账本的系统通常面临两个限制。首先,验证交易需要重新执行它所证明的状态转换。其次,交易不仅揭示了哪个应用程序进行了状态转换,还揭示了应用程序的内部状态。我们设计、实现和评估了 ZEXE,这是一个基于账本的系统,用户可以在其中执行离线计算并随后生成交易,证明这些计算的正确性,满足两个主要属性。首先,交易隐藏了有关离线计算的所有信息。其次,无论离线计算如何,任何人都可以在恒定时间内验证交易。ZEXE 的核心是我们引入的新密码原语的构造,即去中心化私有计算(DPC)方案。为了高效地实现我们的构造,我们利用了密码学证明领域的工具,包括简洁的零知识证明和递归证明组合。总体而言,无论离线计算如何,ZEXE 中的交易都是 968 字节,生成交易的时间不到 1 分钟,加上随着离线计算而增长的时间。我们演示如何使用 ZEXE 实现流行应用程序的隐私保护类似物:用户定义的私有资产和这些资产的私有去中心化交易所。
Ledger-based systems that support rich applications often suffer from two limitations. First, validating a transaction requires re-executing the state transition that it attests to. Second, transactions not only reveal which application had a state transition but also reveal the application’s internal state.We design, implement, and evaluate ZEXE, a ledger-based system where users can execute offline computations and subsequently produce transactions, attesting to the correctness of these computations, that satisfy two main properties. First, transactions hide all information about the offline computations. Second, transactions can be validated in constant time by anyone, regardless of the offline computation.The core of ZEXE is a construction for a new cryptographic primitive that we introduce, decentralized private computation (DPC) schemes. In order to achieve an efficient implementation of our construction, we leverage tools in the area of cryptographic proofs, including succinct zero knowledge proofs and recursive proof composition. Overall, transactions in ZEXE are 968 bytes regardless of the offline computation, and generating them takes less than 1min plus a time that grows with the offline computation.We demonstrate how to use ZEXE to realize privacy-preserving analogues of popular applications: private user-defined assets and private decentralized exchanges for these assets.