2026-03-30T10:29:43Z
2026-03-30T10:29:43Z
2024
2026-03-30T10:29:43Z
Zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs) are the most efficient proof systems in terms of proof size and verification. Currently, Groth's scheme from EUROCRYPT 2016, Groth16 , is the state-of-the-art and is widely deployed in practice. Groth16 is originally proven to achieve knowledge soundness, which does not guarantee the non-malleability of proofs. There has been considerable progress in presenting new zk-SNARKs or modifying Groth16 to efficiently achieve strong Simulation extractability, which is shown to be a necessary requirement in some applications. In this paper, we revise the Random oracle based variant of Groth16 proposed by Bowe and Gabizon, BG18, the most efficient one in terms of prover efficiency and CRS size among the candidates, and present a more efficient variant that saves 2 pairings in the verification and 1 group element in the proof. This supersedes our preliminary construction, presented in CANS 2020 (Baghery et al. in CANS 20, volume 12579 of LNCS, Springer, Heidelberg. pp 453-461, 2020), which saved 1 pairing in the verification, and was proven in the generic group model. Our new construction also improves on BG18 in that our proofs are in the algebraic group model with Random Oracles and reduces security to standard computational assumptions in bilinear groups (as opposed to using the full power of the generic group model (GGM)). We implement our proposed simulation extractable zk-SNARK (SE zk-SNARK) along with BG18 in the Arkworks library, and compare the efficiency of our scheme with some related works. Our empirical experiences confirm that our SE zk-SNARK is more efficient than all previous simulation extractable (SE) schemes in most dimensions and it has very close efficiency to the original Groth16 .
We thank Alonso González for his helpful discussions and the reviewers for their valuable comments. Karim Baghery has been supported in part by the Defense Advanced Research Projects Agency (DARPA) under contract No. HR001120C0085, by the FWO under an Odysseus project GOH9718N, and by CyberSecurity Research Flanders with reference number VR20192203. Carla Ràfols was partially supported by Project RTI2018-102112-B-I00 (AEI / FEDER, UE).
Article
Published version
English
NIZK; Zk-SNARK; Strong simulation extractability; Algebraic group model; Random oracle model
Springer
International Journal of Information Security. 2024 Feb;23(1):431-45
info:eu-repo/grantAgreement/ES/2PE/RTI2018-102112-B-I00
This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
http://creativecommons.org/licenses/by/4.0/