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Efficient Secure Outsourcing Computation of Matrix Multiplication in Cloud Computing

Authors: Shenmin Zhang; Hongwei Li 0001; Kun Jia; Yuan-Shun Dai; Lian Zhao;

Efficient Secure Outsourcing Computation of Matrix Multiplication in Cloud Computing

Abstract

With development of outsourcing computation, it is possible for clients with limited computing resources to outsource heavy computational tasks to the cloud server and thus relieve huge burden of the client. As continuous attention of delegation in recent years, requirements of security and efficiency are badly concerned undoubtedly, especially for matrix multiplication. Considering wide applications of matrix multiplication, e.g. graph processing and large date processing, in this paper, we present an identity-based publicly verifiable delegation scheme in amortized model which meets the need of security and efficiency both. Moreover, by using an secure encryption algorithm and a verification certification, the security analysis of the proposed scheme demonstrates the privacy of matrixes involved and the correctness. To demonstrate efficient properties, we compared our scheme with some existing works in terms of functionality as well as computation, storage and communication overhead.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Top 10%
Top 10%
Top 10%
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