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HEAX: An Architecture for Computing on Encrypted Data
arXiv - CS - Hardware Architecture Pub Date : 2019-09-20 , DOI: arxiv-1909.09731
M. Sadegh Riazi and Kim Laine and Blake Pelton and Wei Dai

With the rapid increase in cloud computing, concerns surrounding data privacy, security, and confidentiality also have been increased significantly. Not only cloud providers are susceptible to internal and external hacks, but also in some scenarios, data owners cannot outsource the computation due to privacy laws such as GDPR, HIPAA, or CCPA. Fully Homomorphic Encryption (FHE) is a groundbreaking invention in cryptography that, unlike traditional cryptosystems, enables computation on encrypted data without ever decrypting it. However, the most critical obstacle in deploying FHE at large-scale is the enormous computation overhead. In this paper, we present HEAX, a novel hardware architecture for FHE that achieves unprecedented performance improvement. HEAX leverages multiple levels of parallelism, ranging from ciphertext-level to fine-grained modular arithmetic level. Our first contribution is a new highly-parallelizable architecture for number-theoretic transform (NTT) which can be of independent interest as NTT is frequently used in many lattice-based cryptography systems. Building on top of NTT engine, we design a novel architecture for computation on homomorphically encrypted data. We also introduce several techniques to enable an end-to-end, fully pipelined design as well as reducing on-chip memory consumption. Our implementation on reconfigurable hardware demonstrates 164-268x performance improvement for a wide range of FHE parameters.

中文翻译:

HEAX:加密数据计算架构

随着云计算的快速增长,对数据隐私、安全和机密性的关注也显着增加。不仅云提供商容易受到内部和外部黑客攻击,而且在某些情况下,由于 GDPR、HIPAA 或 CCPA 等隐私法,数据所有者无法将计算外包。全同态加密 (FHE) 是密码学领域的一项突破性发明,与传统密码系统不同,它无需解密即可对加密数据进行计算。然而,大规模部署 FHE 的最关键障碍是巨大的计算开销。在本文中,我们介绍了 HEAX,这是一种新颖的 FHE 硬件架构,可实现前所未有的性能提升。HEAX 利用多级并行性,从密文级别到细粒度的模块化算术级别。我们的第一个贡献是一种用于数论变换 (NTT) 的新的高度可并行化架构,由于 NTT 经常用于许多基于格的密码系统,因此该架构具有独立意义。基于 NTT 引擎,我们设计了一种新颖的架构来计算同态加密数据。我们还介绍了几种技术来实现端到端、完全流水线化的设计以及减少片上内存消耗。我们在可重新配置硬件上的实现展示了对各种 FHE 参数的 164-268 倍性能提升。我们的第一个贡献是一种用于数论变换 (NTT) 的新的高度可并行化架构,由于 NTT 经常用于许多基于格的密码系统,因此该架构具有独立意义。基于 NTT 引擎,我们设计了一种新颖的架构来计算同态加密数据。我们还介绍了几种技术来实现端到端、完全流水线化的设计以及减少片上内存消耗。我们在可重新配置硬件上的实现展示了对各种 FHE 参数的 164-268 倍性能提升。我们的第一个贡献是一种用于数论变换 (NTT) 的新的高度可并行化架构,由于 NTT 经常用于许多基于格的密码系统,因此该架构具有独立意义。基于 NTT 引擎,我们设计了一种新颖的架构来计算同态加密数据。我们还介绍了几种技术来实现端到端、完全流水线化的设计以及减少片上内存消耗。我们在可重新配置硬件上的实现展示了对各种 FHE 参数的 164-268 倍性能提升。完全流水线设计以及减少片上内存消耗。我们在可重新配置硬件上的实现展示了对各种 FHE 参数的 164-268 倍性能提升。完全流水线设计以及减少片上内存消耗。我们在可重新配置硬件上的实现展示了对各种 FHE 参数的 164-268 倍性能提升。
更新日期:2020-01-27
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