Faster PCA and linear regression through hypercubes in HElib

Deevashwer Rathee, Pradeep Kumar Mishra, Masaya Yasuda

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

1 Citation (Scopus)

Abstract

The significant advancements in the field of homomorphic encryption have led to a grown interest in securely outsourcing data and computation for privacy critical applications. In this paper, we focus on the problem of performing secure predictive analysis, such as principal component analysis (PCA) and linear regression, through exact arithmetic over encrypted data. We improve the plaintext structure of Lu et al.'s protocols (from NDSS 2017), by switching over from linear array arrangement to a two-dimensional hypercube. This enables us to utilize the SIMD (Single Instruction Multiple Data) operations to a larger extent, which results in improving the space and time complexity by a factor of matrix dimension. We implement both Lu et al.'s method and ours for PCA and linear regression over HElib, a software library that implements the Brakerski-Gentry-Vaikuntanathan (BGV) homomorphic encryption scheme. In particular, we show how to choose optimal parameters of the BGV scheme for both methods. For example, our experiments show that our method takes 45 seconds to train a linear regression model over a dataset with 32k records and 6 numerical attributes, while Lu et al.'s method takes 206 seconds.

Original languageEnglish
Title of host publicationWPES 2018 - Proceedings of the 2018 Workshop on Privacy in the Electronic Society, co-located with CCS 2018
PublisherAssociation for Computing Machinery
Pages42-53
Number of pages12
ISBN (Electronic)9781450359894
DOIs
Publication statusPublished - Oct 15 2018
Event17th ACM Workshop on Privacy in the Electronic Society, WPES 2018, held in conjunction with the 25th ACM Conference on Computer and Communications Security, CCS 2018 - Toronto, Canada
Duration: Oct 15 2018 → …

Publication series

NameProceedings of the ACM Conference on Computer and Communications Security
ISSN (Print)1543-7221

Other

Other17th ACM Workshop on Privacy in the Electronic Society, WPES 2018, held in conjunction with the 25th ACM Conference on Computer and Communications Security, CCS 2018
CountryCanada
CityToronto
Period10/15/18 → …

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Networks and Communications

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  • Cite this

    Rathee, D., Mishra, P. K., & Yasuda, M. (2018). Faster PCA and linear regression through hypercubes in HElib. In WPES 2018 - Proceedings of the 2018 Workshop on Privacy in the Electronic Society, co-located with CCS 2018 (pp. 42-53). (Proceedings of the ACM Conference on Computer and Communications Security). Association for Computing Machinery. https://doi.org/10.1145/3267323.3268952