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Outsourcing Large Matrix Inversion Computation to A Public Cloud
January-June 2013 (vol. 1 no. 1)
pp. 1
Xinyu Lei, State Key Lab. of Power Transm. Equip. & Syst. Security & New Technol., Chongqing Univ., Chongqing, China
Xiaofeng Liao, State Key Lab. of Power Transm. Equip. & Syst. Security & New Technol., Chongqing Univ., Chongqing, China
Tingwen Huang, Texas A&M Univ. at Qatar, Doha, Qatar
Huaqing Li, State Key Lab. of Power Transm. Equip. & Syst. Security & New Technol., Chongqing Univ., Chongqing, China
Chunqiang Hu, Dept. of Comput. Sci., George Washington Univ., Washington, DC, USA
Cloud computing enables resource-constrained clients to economically outsource their huge computation workloads to a cloud server with massive computational power. This promising computing paradigm inevitably brings in new security concerns and challenges, such as input/output privacy and result verifiability. Since matrix inversion computation (MIC) is a quite common scientific and engineering computational task, we are motivated to design a protocol to enable secure, robust cheating resistant, and efficient outsourcing of MIC to a malicious cloud in this paper. The main idea to protect the privacy is employing some transformations on the original matrix to get a encrypted matrix which is sent to the cloud; and then transforming the result returned from the cloud to get the correct inversion of the original matrix. Next, a randomized Monte Carlo verification algorithm with one-sided error is employed to successfully handle result verification. In this paper, the superiority of this novel technique in designing inexpensive result verification algorithm for secure outsourcing is well demonstrated. We analytically show that the proposed protocol simultaneously fulfills the goals of correctness, security, robust cheating resistance, and high-efficiency. Extensive theoretical analysis and experimental evaluation also show its high-efficiency and immediate practicability.
Index Terms:
Outsourcing,Resource management,Work load management,Cryptography,Privacy,Computational modeling,Cloud computing,Matrix inversion,Outsourcing,Resource management,Work load management,Cryptography,Privacy,Computational modeling,Data Encryption
Citation:
Xinyu Lei, Xiaofeng Liao, Tingwen Huang, Huaqing Li, Chunqiang Hu, "Outsourcing Large Matrix Inversion Computation to A Public Cloud," IEEE Transactions on Cloud Computing, vol. 1, no. 1, pp. 1, Jan.-June 2013, doi:10.1109/TCC.2013.7
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