Privacy-preserving and verifiable protocols for scientific computation outsourcing to the cloud

Computation outsourcing to the cloud has become a popular application in the age of cloud computing. Recently, two protocols for secure outsourcing scientific computations, i.e., linear equation solving and linear programming solving, to the cloud were proposed. In this paper, we improve the work by...

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Published in:	Journal of parallel and distributed computing Vol. 74; no. 3; pp. 2141 - 2151
Main Authors:	Chen, Fei, Xiang, Tao, Yang, Yuanyuan
Format:	Journal Article
Language:	English
Published:	Amsterdam Elsevier Inc 01.03.2014 Elsevier
Subjects:	Applied sciences Cloud computing Computation outsourcing Computer science; control theory; systems Computer systems and distributed systems. User interface Cryptography Distributed computing Exact sciences and technology Information, signal and communications theory Linear equation solving Linear programming Memory and file management (including protection and security) Memory organisation. Data processing Signal and communications theory Software Telecommunications and information theory Cloud computing Linear programming Linear equation solving Distributed computing Computation outsourcing Transmission protocol Pseudorandom number Subcontracting Modeling Homomorphic encryption Multiparty protocol Scientific computation Confidentiality Efficiency Public key Linear transformation Outsourcing Cryptography Computer security Age Random number generation
ISSN:	0743-7315, 1096-0848
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Abstract	Computation outsourcing to the cloud has become a popular application in the age of cloud computing. Recently, two protocols for secure outsourcing scientific computations, i.e., linear equation solving and linear programming solving, to the cloud were proposed. In this paper, we improve the work by proposing new protocols that achieve significant performance gains. For linear equation solving outsourcing, we achieve the improvement by proposing a completely new protocol. The new protocol employs some special linear transformations and there are no homomorphic encryptions and interactions between the client and the cloud, compared with the previous protocol. For linear programming outsourcing, we achieve the improvement by reformulating the linear programming problem in the standard and natural form. We also introduce a method to reduce the key size by using a pseudorandom number generator. The design of the newly proposed protocols also sheds some insight on constructing secure outsourcing protocols for other scientific computations. Comparisons between our protocols and the previous protocols are given, which demonstrate significant improvements of our proposed protocols. We also carry out numerical experiments to validate the efficiency of our protocols for secure linear equation solving and linear programming outsourcing. •Point out a problem in a previous linear equation outsourcing protocol.•Propose new and efficient protocols for linear equation solving and linear programming outsourcing to the cloud.•New protocols improve the performance of previous protocols significantly.•Experimental results validate the new protocols.
AbstractList	Computation outsourcing to the cloud has become a popular application in the age of cloud computing. Recently, two protocols for secure outsourcing scientific computations, i.e., linear equation solving and linear programming solving, to the cloud were proposed. In this paper, we improve the work by proposing new protocols that achieve significant performance gains. For linear equation solving outsourcing, we achieve the improvement by proposing a completely new protocol. The new protocol employs some special linear transformations and there are no homomorphic encryptions and interactions between the client and the cloud, compared with the previous protocol. For linear programming outsourcing, we achieve the improvement by reformulating the linear programming problem in the standard and natural form. We also introduce a method to reduce the key size by using a pseudorandom number generator. The design of the newly proposed protocols also sheds some insight on constructing secure outsourcing protocols for other scientific computations. Comparisons between our protocols and the previous protocols are given, which demonstrate significant improvements of our proposed protocols. We also carry out numerical experiments to validate the efficiency of our protocols for secure linear equation solving and linear programming outsourcing. •Point out a problem in a previous linear equation outsourcing protocol.•Propose new and efficient protocols for linear equation solving and linear programming outsourcing to the cloud.•New protocols improve the performance of previous protocols significantly.•Experimental results validate the new protocols.
Author	Chen, Fei Yang, Yuanyuan Xiang, Tao
Author_xml	– sequence: 1 givenname: Fei surname: Chen fullname: Chen, Fei organization: Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China – sequence: 2 givenname: Tao surname: Xiang fullname: Xiang, Tao email: txiang@cqu.edu.cn organization: College of Computer Science, Chongqing University, Chongqing, China – sequence: 3 givenname: Yuanyuan surname: Yang fullname: Yang, Yuanyuan organization: Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, USA
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Keywords	Cloud computing Linear programming Linear equation solving Distributed computing Computation outsourcing Transmission protocol Pseudorandom number Subcontracting Modeling Homomorphic encryption Multiparty protocol Scientific computation Confidentiality Efficiency Public key Linear transformation Outsourcing Cryptography Computer security Age Random number generation
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Snippet	Computation outsourcing to the cloud has become a popular application in the age of cloud computing. Recently, two protocols for secure outsourcing scientific...
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SubjectTerms	Applied sciences Cloud computing Computation outsourcing Computer science; control theory; systems Computer systems and distributed systems. User interface Cryptography Distributed computing Exact sciences and technology Information, signal and communications theory Linear equation solving Linear programming Memory and file management (including protection and security) Memory organisation. Data processing Signal and communications theory Software Telecommunications and information theory
Title	Privacy-preserving and verifiable protocols for scientific computation outsourcing to the cloud
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