CryptoDB
arkworks: A Rust Ecosystem for Programming zkSNARKs
| Authors: | |
|---|---|
| Download: | |
| Abstract: | zkSNARKs are an exciting avenue for enhancing the privacy and scalability of decentralized systems. Indeed, researchers and practitioners are implementing and deploying decentralized applications atop zkSNARKs at breakneck speed. However, existing zkSNARK implementations live in their own “walled gardens”: optimizations and improvements in one implementation cannot easily be shared with other projects, leading to either inefficiency, or wasted effort due to reimplementation. In this talk, I will introduce *arkworks*: a set of Rust libraries that resolves the foregoing problem by providing all of the components required for zkSNARK programming, packaged into generic, efficient, and easy-to-use modules, such as the following: * Generic implementations of finite fields, elliptic curves, and pairings, as well as instantiations of widely-used curves. * State-of-the-art zkSNARKs such as Groth16, Groth-Maller17, Marlin. * Ergonomic libraries for writing constraints, along with implementations of many commonly-used constraint “gadgets”. * Recursive composition of arbitrary SNARKs, including recursion from accumulation schemes. * Libraries for aggregating proofs and signatures. The modular design of our libraries means that improvements in one component (such as finite field arithmetic) are inherited for free by downstream components (such as zkSNARK implementations). We achieve this composability without sacrificing performance: our generic libraries are competitive with the best application-specific libraries. As a result, our libraries have been deployed in existing industry products such as Celo, MINA, and Aleo. |
BibTeX
@misc{rwc-2022-35508,
title={arkworks: A Rust Ecosystem for Programming zkSNARKs},
howpublished={Talk given at RWC 2022},
author={Pratyush Mishra },
year=2022
}