In Encoding hierarchical classification codes for Privacy-preserving Record Linkage using Bloom filters Rainer Schnell and Christian Borgs introduce encoding Hierarchical classification codes into bloom filters:
Hierarchical classification codes are widely used in many
scientific fields. Such codes might reveal sensitive personal information,
for example medical conditions or occupations. This paper introduces a
new encoding technique for encrypting sensitive codes, which preserves the
hierarchical similarity of the codes. The encoding was developed for the
use of hierarchical codes in Privacy-preserving Record Linkage (PPRL).
The technique is demonstrated with real-world survey data containing
occupational codes (ISCO codes). After describing the construction and
its similarity preserving properties, Hierarchy Preserving Bloom Filters
(HPBF) are compared with positional q-grams and standard Bloom filters
in a PPRL context. The method presented here is similarity preserving
for hierarchies, privacy-preserving and will increase linkage quality when
used in Bloom filter-based PPRL.
schnell2019dina.pdf
This issue is to consider implementing such encoding in clkhash
In Encoding hierarchical classification codes for Privacy-preserving Record Linkage using Bloom filters Rainer Schnell and Christian Borgs introduce encoding Hierarchical classification codes into bloom filters:
schnell2019dina.pdf
This issue is to consider implementing such encoding in clkhash