An Accelerated GPU Library for Homomorphic Encryption Operations of BFV Scheme

被引:6
作者
Turkoglu, Enes Recep [1 ]
Ozcan, Ali Sah [1 ]
Ayduman, Can [1 ]
Mert, Ahmet Can [1 ]
Ozturk, Erdinc [1 ]
Savas, Erkay [1 ]
机构
[1] Sabanci Univ, Fac Engn & Nat Sci, Istanbul, Turkey
来源
2022 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS 22) | 2022年
关键词
Lattice Based Cryptography; Secure Computation; Multiplication; Relinearization; Parallel Processing;
D O I
10.1109/ISCAS48785.2022.9937503
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper presents an accelerated and parallelized GPU implementation for homomorphic encryption operations of the Brakerski-Fan-Vercauteren (BFV) scheme. We improved the run-time performance by optimizing homomorphic multiplication, relinearization, rotation, and addition using Number Theoretic Transform (NTT) and Barrett Reduction and utilizing a Compute Unified Device Architecture (CUDA). To the best of our knowledge, this implementation performs the fastest homomorphic operations in the literature. We used the Simple Encrypted Arithmetic Library (SEAL) version 3.6.6 BFV scheme for implementation on a GPU. Our implementation achieved 13.39x, 47.01x, 39.6x, and 33.71x speedup compared to SEAL running on CPU for addition, multiplication, relinearization, and rotation, respectively for a modulus size of 438-bits and ring degree of 16,384. For the same modulus size and ring degree, this implementation performed one homomorphic multiplication in 1 ms, a relinearization operation in 0.4 ms, a rotation in 0.5 ms, and an addition in 0.017 ms, which demonstrates significant performance improvement over state-of-the-art.
引用
收藏
页码:1155 / 1159
页数:5
相关论文
共 18 条
  • [1] Ahmad Al Badawi AhmadQaisar., 2019, IEEE Transactions on Emerging Topics in Computing
  • [2] [Anonymous], 2010, NVIDIA CUDA C PROGR
  • [3] [Anonymous], 2020, Microsoft SEAL (release 3.6)
  • [4] [Anonymous], 2021, PALISADE LATTICE CRY
  • [5] Bajard J.-C., 2004, SPIE OPTICS PHOTONIC
  • [6] Brakerski Zvika, 2014, ACM Transactions on Computation Theory, V6, DOI 10.1145/2633600
  • [7] EFFICIENT FULLY HOMOMORPHIC ENCRYPTION FROM (STANDARD) LWE
    Brakerski, Zvika
    Vaikuntanathan, Vinod
    [J]. SIAM JOURNAL ON COMPUTING, 2014, 43 (02) : 831 - 871
  • [8] Efficient Multi-Key Homomorphic Encryption with Packed Ciphertexts with Application to Oblivious Neural Network Inference
    Chen, Hao
    Dai, Wei
    Kim, Miran
    Song, Yongsoo
    [J]. PROCEEDINGS OF THE 2019 ACM SIGSAC CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY (CCS'19), 2019, : 395 - 412
  • [9] Accelerating LTV Based Homomorphic Encryption in Reconfigurable Hardware
    Doroz, Yarkin
    Ozturk, Erdinc
    Savas, Erkay
    Sunar, Berk
    [J]. CRYPTOGRAPHIC HARDWARE AND EMBEDDED SYSTEMS - CHES 2015, 2015, 9293 : 185 - 204
  • [10] Fan Junfeng, 2012, Cryptology ePrint Archive, 2012/144