Abstract
The goal of statistical disclosure control (SDC) is to modify statistical data so that it can be published without releasing confidential information that may be linked to specific respondents. The challenge for SDC is to achieve this variation with minimum loss of the detail and accuracy sought by final users. There are many approaches to evaluate the quality of a protection method. However, all these measures are only applicable to numerical or categorical attributes. In this paper, we present some recent results about time series protection and re-identification. We propose a complete framework to evaluate time series protection methods. We also present some empirical results to show how our framework works.
| Original language | English |
|---|---|
| Pages (from-to) | 1663-1677 |
| Number of pages | 15 |
| Journal | Information Sciences |
| Volume | 179 |
| Issue number | 11 |
| DOIs | |
| Publication status | Published - 13 May 2009 |
| Externally published | Yes |
Keywords
- Information loss measures
- Privacy in statistical databases
- Statistical disclosure control
- Time series privacy
Fingerprint
Dive into the research topics of 'Towards the evaluation of time series protection methods'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver