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Paper 2024/1405

VECTIS: Efficient Batching Framework for Group-based CP-SNARKs

Byeongjun Jang, Kookmin University

Gweonho Jeong, Hanyang University

Hyuktae Kwon, Hanyang University

Hyunok Oh, Hanyang University

Abstract

Blockchain applications in finance and identity management increasingly require scalable and privacy-preserving solutions. Cryptographic commitments secure sensitive data on-chain, but verifying properties of these commitments efficiently remains challenging, particularly in large-scale scenarios. For multiple commitments, CP-SNARKs, a family of zk-SNARKs, enhance prover efficiency by shifting large-cost operations outside the circuit and verifying linkages between commitments, but incur verifier-side overhead due to linkage checks. Verification costs grow with the number of commitments, leading to inefficiencies in key size, proof size, and verification time.We propose $\textbf{VECTIS}$, an efficient batching framework for proving multiple commitments. Our approach aggregates multiple commitments into a single batched commitment, enabling the linking proof system to operate on the aggregated commitment instead of individual commitments, thereby significantly reducing the overall verification cost.%streamlining the verification process and improving efficiency.Experimental results show meaningful efficiency gains. For $2^{16}$ commitments, $\textbf{VECTIS}$ reduces the verification time to $0.064$s, achieving over $30\times$ improvement compared to LegoSNARK’s $1.972$s. These results show $\textbf{VECTIS}$’s potential for enabling scalable and efficient privacy-preserving solutions in blockchain applications.

Metadata

Available format(s)

PDF

Category

Cryptographic protocols

Publication info

Preprint.

Keywords

zk-SNARKsSigma protocolImplementationCP-SNARK

Contact author(s)

sunjbs @kookmin ac kr
kwonhojeong @hanyang ac kr
kwonhyuktae00 @gmail com
hoh @hanyang ac kr
jihyek @kookmin ac kr

History

2025-01-25: revised

2024-09-09: received

See all versions

Short URL

https://ia.cr/2024/1405

License

CC BY