Abstract
Increasing efficiency in hospitals is of particular importance. Studies that combine data from multiple hospitals/data holders can tremendously improve the statistical outcome and aid in identifying efficiency markers. However, combining data from multiple 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 privacy preserving linear regression model for the analysis of data coming from several sources. The protocol uses a semi-trusted third party and delivers on privacy and complexity.
| Original language | English |
|---|---|
| Pages (from-to) | 406-414 |
| Number of pages | 9 |
| Journal | CEUR Workshop Proceedings |
| Volume | 1133 |
| Publication status | Published - 2014 |
| Externally published | Yes |
| Event | 2014 Joint Workshops on International Conference on Extending Database Technology, EDBT 2014 and International Conference on Database Theory, ICDT 2014 - Athens, Greece Duration: Mar 28 2014 → … |
Keywords
- Linear regression
- Privacy preserving data mining
- Secure multiparty computation
ASJC Scopus subject areas
- General Computer Science