Harnessing the Cloud for Securely Outsourcing Large-Scale Systems of Linear Equations

Wang, Cong; Ren, Kui; Wang, Jia; Wang, Qian

doi:10.1109/tpds.2012.206

Cited by 136 publications

(67 citation statements)

References 37 publications

(67 reference statements)

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“…To avoid applying FHE and promote efficiency, a lot of papers [9][10][11][12][13][14][15] focused on VC schemes for various kinds of computation and had achieved outstanding results.…”

Section: Verifiable Computation Verifiable Computation (Vc)mentioning

confidence: 99%

Confidentiality-Preserving Publicly Verifiable Computation Schemes for Polynomial Evaluation and Matrix-Vector Multiplication

Sun

Zhu

Qin

et al. 2018

Security and Communication Networks

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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 (CP-PVC) 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.

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“…To avoid applying FHE and promote efficiency, a lot of papers [9][10][11][12][13][14][15] focused on VC schemes for various kinds of computation and had achieved outstanding results.…”

Section: Verifiable Computation Verifiable Computation (Vc)mentioning

confidence: 99%

Confidentiality-Preserving Publicly Verifiable Computation Schemes for Polynomial Evaluation and Matrix-Vector Multiplication

Sun

Zhu

Qin

et al. 2018

Security and Communication Networks

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“…al. [6] introduced a secure outsourcing tool for solving the large-scale system of the linear equations, which is based on the iterative approaches. However, it needs multiround co-operations between the client and the cloud server and thus is quite impractical.…”

Section: Related Workmentioning

confidence: 99%

Secure and Practical Outsourcing of Linear Programming in Cloud Computing: A Survey

Rao¹,

Satyanarayana²

2017

IJCA

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How to protect the data that is processed and generated by the customers, is becoming the major concern in the present day situation. Various engineering, computing and optimization techniques are being used to solve this problem. The investigation has been performed for secure outsourcing of problem for the large-scale systems. In this paper, the essential terms involved in the cloud security has been presented. Whereas, the privacy cheating discouragement "Seccloud", is used for achieving the greater aspects of security. Although the cloud computing is being used to outsource large-scale computations to the cloud, data privacy has become a major issue. In this paper, the modern cryptographic techniques in secure outsourcing along with the research work, which has been proposed in past years, has been presented. Based on some drawback measures, the identification of the problem in the current scenario has been done. This paper also discusses about the motivation towards the problem and our future research directions.

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“…We compare the proposed algorithm with Wang et al's algorithm [22] and Chen et al's algorithm [11]. We denote by M an operation of multiplication, by DE a decryption of Paillier encryption, by L the round of iteration for algorithm [22], and by l a constant.…”

Section: B Comparison Of Three Schemesmentioning

confidence: 99%

“…We denote by M an operation of multiplication, by DE a decryption of Paillier encryption, by L the round of iteration for algorithm [22], and by l a constant. Other operations such as vector additions are omitted in both algorithms.…”

Section: B Comparison Of Three Schemesmentioning

confidence: 99%

“…Not surprisingly, many researchers have devoted considerable effort to seeking for effective methods solve this problem. Recently, Wang et al [22] proposed a secure outsourcing algorithm for largescale system of linear equations, their solution is based on iterative method and Paillier's homomorphic encryption [19] and has the advantage of protecting client's privacy perfectly. However, one fatal disadvantage of Wang et al's algorithm is that it needs multi-round communication between the client C and server S. Specifically, to reach the convergence precision, it may require dozens of (or even hundreds of) iterations for different matrix A by using the iteration methods.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Verifiable Algorithm for Secure Outsourcing of Systems of Linear Equations in the Case of No Solution

Nie¹,

Ma²,

Wang

et al. 2014

2014 Ninth International Conference on Broadband and Wireless Computing, Communication and Applications

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Systems of linear equations, as a fundamental topic in the development of the computational sciences, have been well studied in the scientific community. In this paper, we investigate secure outsourcing for large-scale systems of linear equations, which is considered as a prohibitively expensive computation for the clients with limited computational resources. Based on Chen's work, we propose a verifiable algorithm for secure outsourcing of large-scale systems of linear equations in the case of no solution under the fully malicious model. We uniquely utilize linear programming, which is another well studied scientific computing problem, to help the client to verify the correctness of results returned by the server. Compared with the state-of-the-art algorithm (Chen et al' scheme), the proposed algorithm is suitable not only for any nonsingular dense matrix A, but for a set of singular matrixes that lead the system of linear equations has no solution. Besides, the computational complexity for the verification of no solution in our scheme is still O(n 2 ). Therefore, our proposed algorithm is more suitable for real applications.

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Harnessing the Cloud for Securely Outsourcing Large-Scale Systems of Linear Equations

Cited by 136 publications

References 37 publications

Confidentiality-Preserving Publicly Verifiable Computation Schemes for Polynomial Evaluation and Matrix-Vector Multiplication

Confidentiality-Preserving Publicly Verifiable Computation Schemes for Polynomial Evaluation and Matrix-Vector Multiplication

Secure and Practical Outsourcing of Linear Programming in Cloud Computing: A Survey

Verifiable Algorithm for Secure Outsourcing of Systems of Linear Equations in the Case of No Solution

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