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Boolean Functions with Maximum Algebraic Immunity Based on Properties of Punctured Reed–Muller Codes Read chapter Read first chapter

2016 | OriginalPaper | Chapter

cuHE: A Homomorphic Encryption Accelerator Library

Authors : Wei Dai, Berk Sunar

Published in: Cryptography and Information Security in the Balkans

Publisher: Springer International Publishing

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Abstract

We introduce a CUDA GPU library to accelerate evaluations with homomorphic schemes defined over polynomial rings enabled with a number of optimizations including algebraic techniques for efficient evaluation, memory minimization techniques, memory and thread scheduling and low level CUDA hand-tuned assembly optimizations to take full advantage of the mass parallelism and high memory bandwidth GPUs offer. The arithmetic functions constructed to handle very large polynomial operands using number-theoretic transform (NTT) and Chinese remainder theorem (CRT) based methods are then extended to implement the primitives of the leveled homomorphic encryption scheme proposed by López-Alt, Tromer and Vaikuntanathan. To compare the performance of the proposed CUDA library we implemented two applications: the Prince block cipher and homomorphic sorting algorithms on two GPU platforms in single GPU and multiple GPU configurations. We observed a speedup of 25 times and 51 times over the best previous GPU implementation for Prince with single and triple GPUs, respectively. Similarly for homomorphic sorting we obtained 12–41 times speedup depending on the number and size of the sorted elements.

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previous chapter On the Efficiency of Polynomial Multiplication for Lattice-Based Cryptography on GPUs Using CUDA
next chapter Extended Functionality in Verifiable Searchable Encryption
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Metadata
Title
cuHE: A Homomorphic Encryption Accelerator Library
Authors
Wei Dai
Berk Sunar
Copyright Year
2016
Book
Cryptography and Information Security in the Balkans

Print ISBN: 978-3-319-29171-0

Electronic ISBN: 978-3-319-29172-7

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-29172-7_11

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