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用于统计建模的全同态加密

Fully Homomorphic Encryption for Statistical Modeling

Balasubramanian Narasimhan

arXiv 2610.04163首次发表:更新:

AI 中文总结

本文提出利用R包openfhe.R和homomorpheR实现全同态加密下的统计建模,支持加密算术与多参与方协议,并通过分布式Cox回归和联邦Cox-lasso验证其可行性。

AI 中文摘要

全同态加密允许对加密值进行算术运算,因此执行计算的方无需查看其操作的数据。这在协作方或站点无法共享数据记录或计算摘要但仍需进行联合分析的情况下非常有用。我们通过R中的两个包(一个广泛用于应用统计的平台)演示了可重复执行此类分析所需的协议。第一个是openfhe.R,它是OpenFHE C++库的接口,提供精确整数算术(BFV、BGV)、近似实值算术(CKKS)、布尔电路和多参与方密钥生成。第二个是homomorpheR,它在第一个包之上为多参与方协议构建了一小组主/从原语。两者结合,允许普通的R统计例程在函数值边界与加密算术层组合,前提是跨越该边界的量可分解为各站点的总和。我们提出了两项验证研究:分布式分层Cox回归,其中stats4::mle()通过加密通道收敛;以及通过共识ADMM的凸优化进行联邦Cox-lasso,其中跨站点更新是唯一加密的步骤。我们还讨论了联邦相似性检索和两方预测。在整个过程中,假设参与方是诚实但好奇的,并且阈值密钥生成消除了任何单一方持有可用密钥的假设。

英文摘要

Fully homomorphic encryption allows arithmetic to be carried out on encrypted values, so that a party performing a computation need not see the data it operates on. This is useful wherever collaborating parties or sites cannot share data records or computed summaries yet need to do a joint analysis. We demonstrate the protocols needed to perform such analyses reproducibly via two packages in R, a platform widely used for applied statistics. The first, openfhe.R, is an interface to the OpenFHE C++ library, which exposes exact integer arithmetic (BFV, BGV), approximate real-valued arithmetic (CKKS), Boolean circuits, and multiparty key generation. The second is homomorpheR, which builds a small set of master/worker primitives for multi-party protocols on top of the first. Together, the two let an ordinary R statistical routine compose with an encrypted-arithmetic layer at the function-value boundary, provided the quantity crossing that boundary decomposes as a sum over sites. Two validation studies are presented: distributed stratified Cox regression, where stats4::mle() converges through an encrypted channel, and federated Cox-lasso via convex optimization using consensus ADMM, where the cross-site update is the only encrypted step. We also discuss federated similarity retrieval and two-party prediction. Throughout, the parties are assumed honest-but-curious, and threshold key generation removes the assumption that any single party holds a usable secret key.

Comments39 pages, 6 figures, 8 tables

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