Abstract
Background: Privacy-preserving record linkage (PPRL) is the process of
detecting dataset entries that refer to the same individual within two independent
datasets, without disclosing any personal information. While applied in different
fields, it particularly attained importance in the medical sector. One popular PPRL
method are Bloom filters. However, Bloom filters were originally used for encoding
strings only. Objectives: This paper evaluates an encoding method specifically
designed for numerical data and adjusts it for encoding geocoordinates in Bloom
filters. Methods: The proposed numerical encoding of geocoordinates is compared
to the string-based method by using synthetic data. Results: The proposed method
for encoding geocoordinates in Bloom filters attains a higher recall and precision
than the conventional string encoding. Conclusion: Numerical encoding has the
potential of increasing the record linkage quality of Bloom filters, as well as their
privacy level.
Originalsprache | Englisch |
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Titel | dHealth 2020 - Biomedical Informatics for Health and Care |
Redakteure/-innen | Lea Demelius, Karl Kreiner, Dieter Hayn, Michael Nitzlnader, Günter Schreier |
Herausgeber (Verlag) | IOS Press |
Seiten | 23-30 |
Seitenumfang | 8 |
ISBN (Print) | 978-1-64368-085-9 |
DOIs | |
Publikationsstatus | Veröffentlicht - 2020 |
Research Field
- Exploration of Digital Health