Blend arithmetic operations on tensor-based fully homomorphic encryption over real numbers

Keke Gai, Meikang Qiu*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

122 Citations (Scopus)

Abstract

Recent booming growth of networking-based solutions have brought numerous challenges to security and privacy from both perspectives of insider and outsider threats. The encrypted data are relatively considered a safe storage status; however, the process of encrypting data is still facing adversarial actions and data process generally is inapplicable over ciphertexts. As a type of the encryption approach allowing computations over ciphertexts, a fully homomorphic encryption (FHE) can concurrently deal with the adversarial hazards and support computations on ciphertexts. This paper focuses on the issue of blend arithmetic operations over real numbers and proposes a novel tensor-based FHE solution. The proposed approach is called a FHE for blend operations model that uses tensor laws to carry the computations of blend arithmetic operations over real numbers. In our paper, we provide both theoretical proof and experimental evaluations in order to evince the adoptability of the proposed approach.

Original languageEnglish
Article number8169102
Pages (from-to)3590-3598
Number of pages9
JournalIEEE Transactions on Industrial Informatics
Volume14
Issue number8
DOIs
Publication statusPublished - Aug 2018

Keywords

  • Cloud computing
  • Internet-of-Things (IoT)
  • fully homomorphic encryption (FHE)
  • privacy
  • security
  • tensor theory

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