Students and Taxes: a Privacy-Preserving Social Study Using Secure Computation

Dan Bogdanov; Liina Kamm; Baldur Kubo; Reimo Rebane; Ville Sokk; Riivo Talviste

Paper 2015/1159

Students and Taxes: a Privacy-Preserving Social Study Using Secure Computation

Dan Bogdanov, Liina Kamm, Baldur Kubo, Reimo Rebane, Ville Sokk, and Riivo Talviste

Abstract

We describe the use of secure multi-party computation for performing a large-scale privacy-preserving statistical study on real government data. In 2015, statisticians from the Estonian Center of Applied Research (CentAR) conducted a big data study to look for correlations between working during university studies and failing to graduate in time. The study was conducted by linking the database of individual tax payments from the Estonian Tax and Customs Board and the database of higher education events from the Ministry of Education and Research. Data collection, preparation and analysis were conducted using the Sharemind secure multi-party computation system that provided end-to-end cryptographic protection to the analysis. Using ten million tax records and half a million education records in the analysis, this is the largest cryptographically private statistical study ever conducted on real data.

Note: Minor changes and clarifications to the text.

Metadata

Available format(s): PDF
Category: Applications
Publication info: Published elsewhere. Proceedings on Privacy Enhancing Technologies (PoPETs)
DOI: 10.1515/popets-2016-0019
Keywords: secure multi-party computation statistics real-world application
Contact author(s): liina @ cyber ee
History: 2016-02-27: revised; 2015-12-02: received; See all versions
Short URL: https://ia.cr/2015/1159
License: CC BY

BibTeX

@misc{cryptoeprint:2015/1159,
      author = {Dan Bogdanov and Liina Kamm and Baldur Kubo and Reimo Rebane and Ville Sokk and Riivo Talviste},
      title = {Students and Taxes: a Privacy-Preserving Social Study Using Secure Computation},
      howpublished = {Cryptology {ePrint} Archive, Paper 2015/1159},
      year = {2015},
      doi = {10.1515/popets-2016-0019},
      url = {https://eprint.iacr.org/2015/1159}
}