zkVC: Fast Zero-Knowledge Proof for Private and Verifiable Computing

In the context of cloud computing, services are held on cloud servers, where the clients send their data to the server and obtain the results returned by server. However, the computation, data and results are prone to tampering due to the vulnerabilities on the server side. Thus, verifying the integrity of computation is important in the client-server setting. The cryptographic method known as Zero-Knowledge Proof (ZKP) is renowned for facilitating private and verifiable computing. ZKP allows the client to validate that the results from the server are computed correctly without violating the privacy of the server’s intellectual property. Zero-Knowledge Succinct NonInteractive Argument of Knowledge (zkSNARKs), in particular, has been widely applied in various applications like blockchain and verifiable machine learning. Despite their popularity, existing zkSNARKs approaches remain highly computationally intensive. For instance, even basic operations like matrix multiplication require an extensive number of constraints, resulting in significant overhead. In addressing this challenge, we introduce $z k V C$, which optimizes the ZKP computation for matrix multiplication, enabling rapid proof generation on the server side and efficient verification on the client side. zkVC integrates optimized ZKP modules, such as Constraint-reduced Polynomial Circuit (CRPC) and Prefix-Sum Query (PSQ), collectively yielding a more than $\mathbf{1 2}$-fold increase in proof speed over prior methods. The code is available at https://github.com/UCF-Lou-Lab-PET/zkformer.

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Publication Details

Published
2025-06-22
DOI
https://doi.org/10.1109/dac63849.2025.11132681
Citations
2
Primary Topic
Cryptography and Data Security
Type
article
Field-Weighted Citation Impact
4.96
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article

zkVC: Fast Zero-Knowledge Proof for Private and Verifiable Computing

Qian Lou, Yancheng Zhang, Yan Solihin, Lei Ju et al.
2 citations
Cryptography and Data Security
4.96
article

zkVC: Fast Zero-Knowledge Proof for Private and Verifiable Computing

Qian Lou, Yancheng Zhang, Yan Solihin, Lei Ju, Jingtong Hu, Xun Chen, Mengxin Zheng, Weidong Shi
article en
2 citations

Abstract

In the context of cloud computing, services are held on cloud servers, where the clients send their data to the server and obtain the results returned by server. However, the computation, data and results are prone to tampering due to the vulnerabilities on the server side. Thus, verifying the integrity of computation is important in the client-server setting. The cryptographic method known as Zero-Knowledge Proof (ZKP) is renowned for facilitating private and verifiable computing. ZKP allows the client to validate that the results from the server are computed correctly without violating the privacy of the server’s intellectual property. Zero-Knowledge Succinct NonInteractive Argument of Knowledge (zkSNARKs), in particular, has been widely applied in various applications like blockchain and verifiable machine learning. Despite their popularity, existing zkSNARKs approaches remain highly computationally intensive. For instance, even basic operations like matrix multiplication require an extensive number of constraints, resulting in significant overhead. In addressing this challenge, we introduce $z k V C$, which optimizes the ZKP computation for matrix multiplication, enabling rapid proof generation on the server side and efficient verification on the client side. zkVC integrates optimized ZKP modules, such as Constraint-reduced Polynomial Circuit (CRPC) and Prefix-Sum Query (PSQ), collectively yielding a more than $\mathbf{1 2}$-fold increase in proof speed over prior methods. The code is available at https://github.com/UCF-Lou-Lab-PET/zkformer.

University of Central Florida (US), Shandong University (CN), University of Pittsburgh (US), Samsung (United States) (US), Research!America (United States) (US), University of Houston (US)
Openalex Percentile: Top 5%
Cryptography and Data Security
4.96
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