github/awesome-mpc
1
1
Fork 0
mirror of https://github.com/rdragos/awesome-mpc.git synced 2026-01-09 18:17:54 -05:00
Code Issues Packages Projects Releases Wiki Activity

Update readme.md (#73)

Browse Source
This commit is contained in:
Eli Baum
2025-11-18 07:08:23 -05:00
committed by GitHub
parent c7b670bc8b
commit 733a4d86a3
1 changed files with 1 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

1
readme.md
View File

@@ -85,6 +85,7 @@ Here I tried to reference the most recent article found on specific software sin
- [MPyC](https://www.win.tue.nl/%7Eberry/mpyc/) - BGW honest majority multi-party protocol; secure against semi-honest adversaries. | [TPMPC'18](https://www.win.tue.nl/~berry/mpyc/TPMPC2018.pdf). - [MPyC](https://www.win.tue.nl/%7Eberry/mpyc/) - BGW honest majority multi-party protocol; secure against semi-honest adversaries. | [TPMPC'18](https://www.win.tue.nl/~berry/mpyc/TPMPC2018.pdf).
- [Obliv-C](http://oblivc.org/) - 2PC with garbled circuits; secure against semi-honest adversaries. | eprint: [2015/1153](http://eprint.iacr.org/2015/1153). - [Obliv-C](http://oblivc.org/) - 2PC with garbled circuits; secure against semi-honest adversaries. | eprint: [2015/1153](http://eprint.iacr.org/2015/1153).
- [Obliv-Java](https://github.com/Calctopia-OpenSource/jdk10u) - Faithful reimplementation of Java using Obliv-C. | eprint: [2017/878](https://eprint.iacr.org/2017/878) - [Obliv-Java](https://github.com/Calctopia-OpenSource/jdk10u) - Faithful reimplementation of Java using Obliv-C. | eprint: [2017/878](https://eprint.iacr.org/2017/878)
- [ORQ](https://github.com/CASP-Systems-BU/orq) - General framework for relational analytics written in C++; includes fast sorting implementations and supports multiple protocols. | [SOSP'25](https://dl.acm.org/doi/10.1145/3731569.3764833)
- [Rosetta](https://github.com/LatticeX-Foundation/Rosetta/) - 3PC with secret sharing; secure against semi-honest adversaries; focused on reusing the APIs of TensorFlow and allowing to transfer traditional TensorFlow codes into a privacy-preserving manner with minimal changes. - [Rosetta](https://github.com/LatticeX-Foundation/Rosetta/) - 3PC with secret sharing; secure against semi-honest adversaries; focused on reusing the APIs of TensorFlow and allowing to transfer traditional TensorFlow codes into a privacy-preserving manner with minimal changes.
- [SecretFlow-SPU](https://github.com/secretflow/spu) - A domain-specific compiler and runtime suite, that aims to provide a secure computation service with provable security. SPU compiler uses XLA as its front-end Intermediate Representation (IR) and SPU runtime implements various MPC protocols. | [USENIX ATC'23](https://www.usenix.org/system/files/atc23-ma.pdf). - [SecretFlow-SPU](https://github.com/secretflow/spu) - A domain-specific compiler and runtime suite, that aims to provide a secure computation service with provable security. SPU compiler uses XLA as its front-end Intermediate Representation (IR) and SPU runtime implements various MPC protocols. | [USENIX ATC'23](https://www.usenix.org/system/files/atc23-ma.pdf).
- [Sharemind](https://sharemind.cyber.ee/) - 2PC or 3PC with secret sharing; secure against semi-honest adversaries. | [Cyber'13](https://cyber.ee/research/theses/roman_jagomagis_msc.pdf). - [Sharemind](https://sharemind.cyber.ee/) - 2PC or 3PC with secret sharing; secure against semi-honest adversaries. | [Cyber'13](https://cyber.ee/research/theses/roman_jagomagis_msc.pdf).