Paper 2024/1611
Rhombus: Fast Homomorphic Matrix-Vector Multiplication for Secure Two-Party Inference
Abstract
We present
Note: Fix some typos
Metadata
- Available format(s)
- Category
- Applications
- Publication info
- Published elsewhere. Minor revision. ACM CCS 2024
- DOI
- 10.1145/3658644.3690281
- Keywords
- two-party computationsecure inferencehomomorphic matrix multiplicationcoefficient encoding
- Contact author(s)
-
jiaxing hjx @ antgroup com
yangk @ sklc org
tangguofeng gf @ antgroup com
zhangjie hzj @ antgroup com
felix ll @ antgroup com
changzheng wcz @ antgroup com
fuying yy @ antgroup com
wei wangwwei @ antgroup com - History
- 2024-11-05: last of 2 revisions
- 2024-10-10: received
- See all versions
- Short URL
- https://ia.cr/2024/1611
- License
-
CC BY
BibTeX
@misc{cryptoeprint:2024/1611, author = {Jiaxing He and Kang Yang and Guofeng Tang and Zhangjie Huang and Li Lin and Changzheng Wei and Ying Yan and Wei Wang}, title = {Rhombus: Fast Homomorphic Matrix-Vector Multiplication for Secure Two-Party Inference}, howpublished = {Cryptology {ePrint} Archive, Paper 2024/1611}, year = {2024}, doi = {10.1145/3658644.3690281}, url = {https://eprint.iacr.org/2024/1611} }