Design and Implementation of a Homomorphic-Encryption Library

By Shai Halevi, Victor Shoup. 2012

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Hao Chen
2. Kim Laine
3. Wei Dai
4. M. Sadegh Riazi
5. Miran Kim
6. Shai Halevi
7. Jung Hee Cheon
8. Abbas Acar

Citations in the corpus

• XPIR : Private Information Retrieval for Everyone (2016, methodology): “Comparison with [45] The Double-CRT object proposed in [45] is much more elaborated than NTTTools and has many functions needed for fully-homomorphic encryption that we have not implemented.”
• A Survey on Homomorphic Encryption Schemes (2017, methodology): “The design and implementation of HElib are documented in [Halevi and Shoup 2013a] and algorithms used in HElib are documented in [Halevi and Shoup 2014].”
• Simple Encrypted Arithmetic Library - SEAL v2.1 (2016, background): “One reason for this is that the documentation available for HElib [24, 25, 26] does not in general make clear how to select optimal parameters for performance, and in [26, Appendix A] it is noted ‘[t]he BGV implementation in HElib relies on a myriad of parameters .”
• SHIELD: Scalable Homomorphic Implementation of Encrypted Data-Classifiers (2015, methodology): “We observe a 25 × speedup for the secure keyword search on a GPU compared to IBM HElib (and 100 × speedup for circuit depth ≥ 5 as indicated in Fig.”
• An Improved RNS Variant of the BFV Homomorphic Encryption Scheme (2019, background): “, [10,12]), implementing BFV in this manner seems harder.”
• Private genome analysis through homomorphic encryption (2015, methodology): “We used BGV scheme with Shoup-Halevi’s HE library [28] (called HELib).”
• Homomorphic Encryption for Arithmetic of Approximate Numbers (2017, methodology): “[16] suggested a balanced algorithm called the mixed Fourier transform (MFT) and evaluated this algorithm using HElib library [26], but their method is still inefficient because of exponential growth of plaintext modulus and degree in circuit depth.”
• Simple Encrypted Arithmetic Library-SEAL (2017, background): “One reason for this is that the documentation available for HElib [24, 25, 26] does not in general make clear how to select optimal parameters for performance, and in [26, Appendix A] it is noted ‘[t]he BGV implementation in HElib relies on a myriad of parameters ... it takes some experimentation to”
• cuHE: A Homomorphic Encryption Accelerator Library (2015, methodology): “For CPU platforms Halevi and Shoup published the HElib [23], a C++ library for HE that is based on Brakerski-Gentry-Vaikuntanathan (BGV) cryptosystem [2].”