使用完全同态加密的安全数值模拟

IF 3.4 2区 物理与天体物理 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Arseniy Kholod , Yuriy Polyakov , Michael Schlottke-Lakemper
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引用次数: 0

摘要

在对敏感信息(如医疗、金融或工程数据)使用数值模拟时,数据隐私是一个重大问题,尤其是在公共云基础设施等不可信环境中。完全同态加密(FHE)通过直接对加密数据进行安全计算,为实现数据隐私提供了一个很有前途的解决方案。针对计算科学家,这项工作探索了基于fhe的、保护隐私的偏微分方程数值模拟的可行性。该方法采用了一种广泛应用于实数近似计算的FHE方法——Cheon-Kim-Kim-Song (CKKS)方案。介绍了两个Julia包OpenFHE。jl和SecureArithmetic。它封装了OpenFHE c++库,为安全的算术运算提供了一个方便的接口。利用这些工具,评估了OpenFHE中关键FHE操作的准确性和性能,并演示了用加密数据求解线性平流方程的有限差分格式的实现。结果表明,加密安全的数值模拟是可能的,但必须仔细考虑使用FHE带来的计算开销和数值误差。对FHE施加的算法限制的分析强调了将该方法扩展到其他模型和方法的潜在挑战和解决方案。由于CKKS的限制,目前尚不确定该方法能在多大程度上推广到更复杂的算法中,但这些发现为进一步研究保护隐私的科学计算奠定了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Secure numerical simulations using fully homomorphic encryption
Data privacy is a significant concern when using numerical simulations for sensitive information such as medical, financial, or engineering data—especially in untrusted environments like public cloud infrastructures. Fully homomorphic encryption (FHE) offers a promising solution for achieving data privacy by enabling secure computations directly on encrypted data. Aimed at computational scientists, this work explores the viability of FHE-based, privacy-preserving numerical simulations of partial differential equations. The presented approach utilizes the Cheon-Kim-Kim-Song (CKKS) scheme, a widely used FHE method for approximate arithmetic on real numbers. Two Julia packages are introduced, OpenFHE.jl and SecureArithmetic.jl, which wrap the OpenFHE C++ library to provide a convenient interface for secure arithmetic operations. With these tools, the accuracy and performance of key FHE operations in OpenFHE are evaluated, and implementations of finite difference schemes for solving the linear advection equation with encrypted data are demonstrated. The results show that cryptographically secure numerical simulations are possible, but that careful consideration must be given to the computational overhead and the numerical errors introduced by using FHE. An analysis of the algorithmic restrictions imposed by FHE highlights potential challenges and solutions for extending the approach to other models and methods. While it remains uncertain how broadly the approach can be generalized to more complex algorithms due to CKKS limitations, these findings lay the groundwork for further research on privacy-preserving scientific computing.
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来源期刊
Computer Physics Communications
Computer Physics Communications 物理-计算机:跨学科应用
CiteScore
12.10
自引率
3.20%
发文量
287
审稿时长
5.3 months
期刊介绍: The focus of CPC is on contemporary computational methods and techniques and their implementation, the effectiveness of which will normally be evidenced by the author(s) within the context of a substantive problem in physics. Within this setting CPC publishes two types of paper. Computer Programs in Physics (CPiP) These papers describe significant computer programs to be archived in the CPC Program Library which is held in the Mendeley Data repository. The submitted software must be covered by an approved open source licence. Papers and associated computer programs that address a problem of contemporary interest in physics that cannot be solved by current software are particularly encouraged. Computational Physics Papers (CP) These are research papers in, but are not limited to, the following themes across computational physics and related disciplines. mathematical and numerical methods and algorithms; computational models including those associated with the design, control and analysis of experiments; and algebraic computation. Each will normally include software implementation and performance details. The software implementation should, ideally, be available via GitHub, Zenodo or an institutional repository.In addition, research papers on the impact of advanced computer architecture and special purpose computers on computing in the physical sciences and software topics related to, and of importance in, the physical sciences may be considered.
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