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
-
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},
url = {https://eprint.iacr.org/2014/512}
}
