Verifiably private outsourcing scheme for multivariate polynomial evaluation

Yan-li REN; Da-wu GU; Jian-xing CAI; Chun-shui HUANG

doi:10.11959/j.issn.1000-436x.2015172

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Verifiably private outsourcing scheme for multivariate polynomial evaluation

Academic paper | 更新时间：2024-06-05

- Verifiably private outsourcing scheme for multivariate polynomial evaluation
- Journal on Communications Vol. 36, Issue 8, Pages: 23-30(2015)
- 作者机构：
  
  1. 上海大学通信与信息工程学院,上海 200444
  2. 上海交通大学电子信息与电气工程学院,上海 200240
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(61202367);The Doctoral Fund of Ministry of Education of China(20120073110094);The Natural Science Foundation of Shanghai(12ZR1443700);The Innovation Program of Shanghai Municipal Education Commission(14YZ020)
- DOI：10.11959/j.issn.1000-436x.2015172
  CLC： TP309
- Online First：2015-08，
  
  Published：25 August 2015
- 稿件说明：
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Yan-li REN, Da-wu GU, Jian-xing CAI, et al. Verifiably private outsourcing scheme for multivariate polynomial evaluation[J]. Journal on Communications, 2015, 36(8): 23-30.
DOI：

Yan-li REN, Da-wu GU, Jian-xing CAI, et al. Verifiably private outsourcing scheme for multivariate polynomial evaluation[J]. Journal on Communications, 2015, 36(8): 23-30. DOI： 10.11959/j.issn.1000-436x.2015172.

摘要

随着云计算的发展和大数据时代的到来，如何对隐私数据进行外包计算且有效验证计算结果具有重要的现实意义。基于多线性映射和同态加密方案，提出了可验证的多元多项式外包计算方案，用户可准确验证外包计算结果的正确性。方案在标准模型中可证安全，且多项式函数和用户输入对于服务器都是保密的。分析表明，用户计算量远小于服务器的计算代价以及直接计算多项式函数。

Abstract

With the development of cloud computing and big data

it had important practical significance for how to outsource private data and verify the computing result efficiently.A verifiably outsourcing scheme for multivariate polynomial evaluation based on multilinear maps and homomorphic encryption was proposed where the user could verify the computing result exactly.The proposed scheme is provably secure without random oracles and the multivariate polynomial itself and the input of the function are private for the server.Moreover

the cost of the user is much smaller than that of the server

and it is much smaller than that of computing the multivariate polynomial directly.

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references

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