计算的委托私有匹配

Dimitris Mouris, Daniel Masny, Ni Trieu, Shubho Sengupta, Prasad Buddhavarapu, Benjamin M. Case
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引用次数: 2

摘要

计算专用匹配(PMC)在互不信任的双方(C 和 P)拥有的两个数据集之间建立匹配,并允许双方为匹配记录输入更多数据,以进行任意下游安全计算,而无需重新运行专用匹配组件。最先进的 PMC 协议仅支持两方,并假设双方都能参与计算密集型安全计算。我们注意到,这种操作开销限制了这些协议的采用,因为计算能力极低的小型数据所有者或设备将无法参与,因此只有强大的实体才能采用这些协议。我们介绍了两种将 PMC 从 P 方委托给不受信任的云服务器(称为委托方)的协议,允许多个较小的 P 方提供包含标识符和相关值的输入。我们的计算委托私有匹配协议(称为 DPMC 和 DsPMC)基于多个标识符在 C 方和多个委托方 P 的数据集之间建立连接,并计算各方共同标识符的关联值的秘密份额。我们引入了一种可重新随机化的加密遗忘伪随机函数(OPRF)原型,称为 EO,它允许双方对数据进行加密、屏蔽和洗牌。请注意,EO 可能具有独立的意义。我们的 DsPMC 协议结合了 EO 方案和安全的三方洗牌,从而限制了 DPMC 的泄漏。最后,我们的实现证明了我们构建的效率,在整个协议执行过程中,我们的性能大约是相关研究的 10 倍,而在委托人的计算方面,我们的性能至少是相关研究的 20 倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Delegated Private Matching for Compute
Private matching for compute (PMC) establishes a match between two datasets owned by mutually distrusted parties (C and P) and allows the parties to input more data for the matched records for arbitrary downstream secure computation without rerunning the private matching component. The state-of-the-art PMC protocols only support two parties and assume that both parties can participate in computationally intensive secure computation. We observe that such operational overhead limits the adoption of these protocols to solely powerful entities as small data owners or devices with minimal computing power will not be able to participate. We introduce two protocols to delegate PMC from party P to untrusted cloud servers, called delegates, allowing multiple smaller P parties to provide inputs containing identifiers and associated values. Our Delegated Private Matching for Compute protocols, called DPMC and DsPMC, establish a join between the datasets of party C and multiple delegators P based on multiple identifiers and compute secret shares of associated values for the identifiers that the parties have in common. We introduce a rerandomizable encrypted oblivious pseudorandom function (OPRF) primitive, called EO, which allows two parties to encrypt, mask, and shuffle their data. Note that EO may be of independent interest. Our DsPMC protocol limits the leakages of DPMC by combining our EO scheme and secure three-party shuffling. Finally, our implementation demonstrates the efficiency of our constructions by outperforming related works by approximately 10x for the total protocol execution and by at least 20x for the computation on the delegators.
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