Abstract
Studies that combine data from multiple sources can tremendously improve the outcome of the statistical analysis. However, combining data from these various sources for analysis poses privacy risks. A number of protocols have been proposed in the literature to address the privacy concerns; however they do not fully deliver on either privacy or complexity. In this paper, we present a (theoretical) privacy preserving linear regression model for the analysis of data owned by several sources. The protocol uses a semi-trusted third party and delivers on privacy and complexity.
| Original language | English |
|---|---|
| Pages (from-to) | 3-28 |
| Number of pages | 26 |
| Journal | Transactions on Data Privacy |
| Volume | 8 |
| Issue number | 1 |
| Publication status | Published - Jan 1 2015 |
| Externally published | Yes |
ASJC Scopus subject areas
- Software
- Statistics and Probability