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Journal of Ambient Intelligence and Humanized Computing

Improvement and applications of secure outsourcing of scientific computations

Jianhua Yu, Xueli Wang, Wei Gao

Published Apr 21, 2015• 10 citations
Publisher
DOI
10.1007/s12652-015-0280-0

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Matrix calculation plays an important role in both scientific computation and cryptography. Many cryptographic protocols, scientific computations, and numerical computations are based on matrix calculation. However, it is difficult to finish matrix calculation independently for these customers whose computation abilities are limited. Cloud Computing has a great deal of computational resources, which enable customers with limited computational resources to outsource their mass computing to the cloud. In this paper we design secure, verifiable, and practical outsourcing protocols for matrix calculation, including matrix multiplication, computing the determinant and inverse of a matrix. Compared with those existing outsourcing protocols, our protocols have obvious improvement concerning both efficiency and security. Furthermore, no cryptographic assumption is needed in our protocols. Finally, we give two applications for our outsourcing protocols; one is to construct an outsourcing protocol for solving the large-scale systems of linear equations, and the other is to design an outsourcing protocol for realizing a cryptosystem based on error-correction code.

Scientia Sinica Informationis•Jul 1, 2013•3 citations
Matrix calculation plays an important role in both scientific computation and cryptography. Many cryptographic protocols, scientific computations, and numerical computations are based on matrix calculation. However, it is difficult to finish matrix calculation independently for these customers whose computation abilities are limited. Cloud Computing has a great deal of computational resources, which enable customers with limited computational resources to outsource their mass computing to the cloud. In this paper we design secure, verifiable, and practical outsourcing protocols for matrix calculation, including matrix multiplication, computing the determinant and inverse of a matrix. Compared with those existing outsourcing protocols, our protocols have obvious improvement concerning both efficiency and security. Furthermore, no cryptographic assumption is needed in our protocols. Finally, we give two applications for our outsourcing protocols; one is to construct an outsourcing protocol for solving the large-scale systems of linear equations, and the other is to design an outsourcing protocol for realizing a cryptosystem based on error-correction code.