## Cryptology ePrint Archive: Report 2014/512

Rmind: a tool for cryptographically secure statistical analysis

Dan Bogdanov and Liina Kamm and 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.

Category / Keywords: implementation / Privacy, statistical analysis, hypothesis testing, predictive modelling

Date: received 30 Jun 2014, last revised 3 Dec 2014

Contact author: liina at cyber ee

Available format(s): PDF | BibTeX Citation

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

Short URL: ia.cr/2014/512

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