Confidentiality-preserving publicly verifiable computation schemes for polynomial evaluation and matrix-vector multiplication
Sun, Jiameng ORCID: 0000-0003-3153-7698 , Zhu, Binrui, Qin, Jing ORCID: 0000-0003-2380-0396 , Hu, Jiankun ORCID: 0000-0003-0230-1432 and Ma, Jixin (2018) Confidentiality-preserving publicly verifiable computation schemes for polynomial evaluation and matrix-vector multiplication. Security and Communication Networks, 2018:5275132. ISSN 1939-0114 (Print), 1939-0122 (Online) (doi:https://doi.org/10.1155/2018/5275132)
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24385 MA_Confidentiality-preserving_Publicly_Verifiable_Computation_Schemes_For_Polynomial_Evaluation_(OA)_2018.pdf - Published Version Available under License Creative Commons Attribution. Download (1MB) | Preview |
Abstract
With the development of cloud services, outsourcing computation tasks to a commercial cloud server has drawn attention of various communities, especially in the Big Data era. Public verifiability offers a flexible functionality in real circumstance where the cloud service provider (CSP) may be untrusted or some malicious users may slander the CSP on purpose. However, sometimes the computational result is sensitive and is supposed to remain undisclosed in the public verification phase, while existing works on publicly verifiable computation (PVC) fail to achieve this requirement. In this paper, we highlight the property of result confidentiality in publicly verifiable computation and present confidentiality-preserving public verifiable computation (CPPVC) schemes for multivariate polynomial evaluation and matrix-vector multiplication, respectively. The proposed schemes work efficiently under the amortized model and, compared with previous PVC schemes for these computations, achieve confidentiality of computational results, while maintaining the property of public verifiability. The proposed schemes proved to be secure, efficient, and result-confidential. In addition, we provide the algorithms and experimental simulation to show the performance of the proposed schemes, which indicates that our proposal is also acceptable in practice.
Item Type: | Article |
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Uncontrolled Keywords: | public verifiability, confidentiality-preserving public verifiable computation (CPPVC), multivariate polynomial evaluation, matrix-vector multiplication |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Faculty / School / Research Centre / Research Group: | Faculty of Liberal Arts & Sciences > Computational Science & Engineering Group (CSEH) Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS) Faculty of Engineering & Science |
Last Modified: | 04 Mar 2022 13:06 |
URI: | http://gala.gre.ac.uk/id/eprint/24385 |
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