HEAX: High-Performance Architecture for Computation on Homomorphically Encrypted Data in the Cloud

by   M. Sadegh Riazi, et al.

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.


page 7

page 8

page 9

page 10

page 11


HEAX: An Architecture for Computing on Encrypted Data

With the rapid increase in cloud computing, concerns surrounding data pr...

Hardware Acceleration for Third-Generation FHE and PSI Based on It

With the expansion of cloud services, serious concerns about the privacy...

Survey on Secure Search Over Encrypted Data on the Cloud

Cloud computing has become a potential resource for businesses and indiv...

The AlexNet Moment for Homomorphic Encryption: HCNN, the First Homomorphic CNN on Encrypted Data with GPUs

Fully homomorphic encryption, with its widely-known feature of computing...

CoFHEE: A Co-processor for Fully Homomorphic Encryption Execution

The migration of computation to the cloud has raised privacy concerns as...

HEAAN Demystified: Accelerating Fully Homomorphic Encryption Through Architecture-centric Analysis and Optimization

Homomorphic Encryption (HE) draws a significant attention as a privacy-p...

ERIC: An Efficient and Practical Software Obfuscation Framework

Modern cloud computing systems distribute software executables over a ne...