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Enabling efficient and secure outsourcing of large matrix multiplications

Version 2 2024-06-03, 07:31
Version 1 2016-05-24, 17:39
conference contribution
posted on 2024-06-03, 07:31 authored by K Jia, H Li, D Liu, S Yu
With the growing popularity of cloud computing, outsourced computing has attracted much research effort recently. A computationally weak client is capable of delegating its heavy computing tasks, such as large matrix multiplications, to the cloud server. Critical requirements for such tasks include the need to guarantee the unforgeability of computing results and the preservation of the privacy of clients. On one hand, the result computed by the cloud server needs to be verified since the cloud server cannot be fully honest. On the other hand, as the data involved in computing may contain some sensitive information of the client, the data should not be identified by the cloud server. In this paper, we address these above issues by developing an Efficient and Secure Outsourcing scheme for Large Matrix Multiplication, named ESO- LMM. Security analysis demonstrates that ESO-LMM achieves the security requirements in terms of unforgeability of proof and privacy protection of outsourced data. Furthermore, performance evaluation indicates that ESO-LMM is much more efficient compared with the existing works in terms of computation, communication and storage overhead.

History

Pagination

1-6

Location

San Diego, California

Start date

2015-12-06

End date

2015-12-09

ISBN-13

9781479959525

Language

eng

Publication classification

E Conference publication, E1 Full written paper - refereed

Copyright notice

2015, IEEE

Title of proceedings

GLOBECOM 2015: Proceedings of the IEEE Global Communications Conference

Event

IEEE Global Communications. Conference (2015: San Diego, California)

Publisher

IEEE

Place of publication

Piscataway, N.J.

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