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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Privacy Preserving Group Linkage
verfasst von : Fengjun Li, Yuxin Chen, Bo Luo, Dongwon Lee, Peng Liu
Erschienen in: Scientific and Statistical Database Management
Verlag: Springer Berlin Heidelberg
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The problem of privacy preserving record linkage is to find the intersection of records from two parties, while not revealing any private records to each other. Recently, group linkage has been introduced to measure the similarity of groups of records [19]. When we extend the traditional privacy preserving record linkage methods to group linkage measurement, group membership privacy becomes vulnerable – record identity could be discovered from unlinked groups. In this paper, we introduce threshold privacy preserving group linkage (TPPGL) schemes, in which both parties only learn whether or not the groups are linked. Therefore, our approach is secure under
group membership inference attacks
. In experiments, we show that using the proposed TPPGL schemes, group membership privacy is well protected against inference attacks with a reasonable overhead.