Secure Dimensionality Reduction: Applying Linear Discriminant Analysis over the TFHE Homomorphic Encryption Scheme

  • Geonwoo Jeon*
  • , Mi Yeon Hong
  • , Joon Soo Yoo
  • , Ji Won Yoon
  • , Baekkyung Song
  • *Corresponding author for this work

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

Abstract

In the context of the proliferating AI landscape, driven by entities like ChatGPT, the demand for extensive data utilization for training has surged, raising concerns about unauthorized data aggregation and privacy breaches. Paradoxically, this surge in data consumption has raised a critical concern - the breach of privacy stemming from unauthorized data aggregation. Sensitive data categories, including credit card details, medical records, and geographical locations, are particularly vulnerable to misuse. Homomorphic Encryption (HE), a post-quantum attack-resistant cryptographic technique, addresses this concern by enabling secure computations on encrypted data. However, HE's potential is hindered by limitations in evaluation speed, particularly evident in high-dimensional data analysis. This paper introduces contributions, including efficient inverse matrix computation, tailored eigenvector extraction via the power method for the TFHE scheme, and eigenvalue calculation using the Rayleigh quotient within TFHE. The feasibility of applying LDA in the encrypted domain is demonstrated using Fast Fully Homomorphic Encryption over the Torus (TFHE) scheme.

Original languageEnglish
Title of host publicationICTC 2023 - 14th International Conference on Information and Communication Technology Convergence
Subtitle of host publicationExploring the Frontiers of ICT Innovation
PublisherIEEE Computer Society
Pages1462-1467
Number of pages6
ISBN (Electronic)9798350313277
DOIs
Publication statusPublished - 2023
Event14th International Conference on Information and Communication Technology Convergence, ICTC 2023 - Jeju Island, Korea, Republic of
Duration: 2023 Oct 112023 Oct 13

Publication series

NameInternational Conference on ICT Convergence
ISSN (Print)2162-1233
ISSN (Electronic)2162-1241

Conference

Conference14th International Conference on Information and Communication Technology Convergence, ICTC 2023
Country/TerritoryKorea, Republic of
CityJeju Island
Period23/10/1123/10/13

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

  • Homomorphic Encryption
  • Linear Discriminant Analysis
  • Newton's method
  • Power method
  • TFHE

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications

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