A secure and verifiable outsourcing scheme for matrix inverse computation

Chunqiang Hu, Abdulrahman Alhothaily, Arwa Alrawais, Xiuzhen Cheng, Carl Sturtivant, Hang Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

33 Scopus citations


Matrix inverse computation is one of the most fundamental mathematical problems in large-scale data analytics and computing. It is often too expensive to be solved in resource-constrained devices such as sensors. Outsourcing the computation task to a cloud server or a fog server is a potential approach as the server is able to perform large-scale scientific computations on behalf of resource-constrained users with special software. However, outsourcing brings in new security concerns and challenges such as data privacy violations and result invalidation. In this paper, we propose a secure and verifiable outsourcing scheme to compute the matrix inverse in a server. In our scheme, the client generates two secret key sets based on two chaotic systems, which are utilized to create two sparse matrices whose permuted versions are used for matrix encryption and decryption to protect input and output privacy. The server computes the inverse over the ciphertext matrix and returns the result to the client who can verify the validity of the inverse. We analyze the proposed scheme in terms of correctness, security, verifiability, and attack resistance, and compare its performance (computation, storage, and communication overheads) with those of the state-of-the-art. Our theoretical results and comparison study demonstrate that the proposed scheme provides a secure and efficient outsourcing mechanism for matrix inverse computation.

Original languageEnglish (US)
Title of host publicationINFOCOM 2017 - IEEE Conference on Computer Communications
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509053360
StatePublished - Oct 2 2017
Event2017 IEEE Conference on Computer Communications, INFOCOM 2017 - Atlanta, United States
Duration: May 1 2017May 4 2017

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X


Other2017 IEEE Conference on Computer Communications, INFOCOM 2017
Country/TerritoryUnited States

Bibliographical note

Funding Information:
This research was partially supported by the National Science Foundation of the US under grants CNS-1318872, CCF-1442642, IIS-1343976, AST-1443773, and CNS-1624485, and the National Natural Science Foundation of China under grants 61672119.


  • Chaotic systems
  • Cloud/fog computing
  • Data privacy
  • Matrix inversion
  • Secure outsourcing
  • Verification


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