Paper 2014/512

Rmind: a tool for cryptographically secure statistical analysis

Dan Bogdanov, Liina Kamm, Sven Laur, and Ville Sokk

Abstract

Secure multi-party computation platforms are becoming more and more practical. This has paved the way for privacy-preserving statistical analysis using secure multi-party computation. Simple statistical analysis functions have been emerging here and there in literature, but no comprehensive system has been compiled. We describe and implement the most used statistical analysis functions in the privacy-preserving setting including simple statistics, t-test, $\chi^{2}$ test, Wilcoxon tests and linear regression. We give descriptions of the privacy-preserving algorithms and benchmark results that show the feasibility of our solution.

Note: Worded the security requirements better. The rest of the paper updated according to new requirements.

Metadata
Available format(s)
PDF
Category
Implementation
Publication info
Preprint. MINOR revision.
Keywords
Privacystatistical analysishypothesis testingpredictive modelling
Contact author(s)
liina @ cyber ee
History
2014-12-03: revised
2014-06-30: received
See all versions
Short URL
https://ia.cr/2014/512
License
Creative Commons Attribution
CC BY

BibTeX

@misc{cryptoeprint:2014/512,
      author = {Dan Bogdanov and Liina Kamm and Sven Laur and Ville Sokk},
      title = {Rmind: a tool for cryptographically secure statistical analysis},
      howpublished = {Cryptology ePrint Archive, Paper 2014/512},
      year = {2014},
      note = {\url{https://eprint.iacr.org/2014/512}},
      url = {https://eprint.iacr.org/2014/512}
}
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