The Fast Paillier Decryption with Montgomery Modular Multiplication Based on OpenMP

Decong Lin, Hongbo Cao, Chunzi Tian, Yongqi Sun
{"title":"The Fast Paillier Decryption with Montgomery Modular Multiplication Based on OpenMP","authors":"Decong Lin, Hongbo Cao, Chunzi Tian, Yongqi Sun","doi":"10.1109/PAAP56126.2022.10010630","DOIUrl":null,"url":null,"abstract":"With the increasing awareness of privacy protection and data security, people’s concerns over the confidentiality of sensitive data still limit the application of distributed artificial intelligence. In fact, a new encryption form, called homomorphic encryption(HE), has achieved a balance between security and operability. In particular, one of the HE schemes named Paillier has been adopted to protect data privacy in distributed artificial intelligence. However, the massive computation of modular multiplication in Paillier greatly affects the speed of encryption and decryption. In this paper, we propose a fast CRT-Paillier scheme to accelerate its decryption process. We first introduce the Montgomery algorithm to the CRT-Paillier to improve the process of the modular exponentiation, and then compute the modular exponentiation in parallel by using OpenMP. The experimental results show that our proposed scheme has greatly heightened its decryption speed while preserving the same security level. Especially, when the key length is 4096-bit, its speed of decryption is about 148 times faster than CRT-Paillier.","PeriodicalId":336339,"journal":{"name":"2022 IEEE 13th International Symposium on Parallel Architectures, Algorithms and Programming (PAAP)","volume":"37 11","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 13th International Symposium on Parallel Architectures, Algorithms and Programming (PAAP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PAAP56126.2022.10010630","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

With the increasing awareness of privacy protection and data security, people’s concerns over the confidentiality of sensitive data still limit the application of distributed artificial intelligence. In fact, a new encryption form, called homomorphic encryption(HE), has achieved a balance between security and operability. In particular, one of the HE schemes named Paillier has been adopted to protect data privacy in distributed artificial intelligence. However, the massive computation of modular multiplication in Paillier greatly affects the speed of encryption and decryption. In this paper, we propose a fast CRT-Paillier scheme to accelerate its decryption process. We first introduce the Montgomery algorithm to the CRT-Paillier to improve the process of the modular exponentiation, and then compute the modular exponentiation in parallel by using OpenMP. The experimental results show that our proposed scheme has greatly heightened its decryption speed while preserving the same security level. Especially, when the key length is 4096-bit, its speed of decryption is about 148 times faster than CRT-Paillier.
基于OpenMP的Montgomery模乘法快速Paillier解密
随着人们对隐私保护和数据安全意识的提高,人们对敏感数据保密性的担忧仍然限制了分布式人工智能的应用。事实上,一种新的加密形式,称为同态加密(HE),已经在安全性和可操作性之间取得了平衡。特别是在分布式人工智能中,采用了一种名为Paillier的HE方案来保护数据隐私。然而,在Paillier中,模乘法的大量计算极大地影响了加密和解密的速度。本文提出了一种快速CRT-Paillier方案来加速其解密过程。首先将Montgomery算法引入到CRT-Paillier中,改进模幂运算过程,然后利用OpenMP并行计算模幂运算。实验结果表明,该方案在保持相同安全级别的前提下,大大提高了解密速度。特别是当密钥长度为4096位时,其解密速度比CRT-Paillier快约148倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信