Privacy Preserving Group Linkage

  • Fengjun Li
  • Yuxin Chen
  • Bo Luo
  • Dongwon Lee
  • Peng Liu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6809)


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.


Group linkage privacy secure multi-party computation 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Fengjun Li
    • 1
  • Yuxin Chen
    • 1
  • Bo Luo
    • 1
  • Dongwon Lee
    • 2
  • Peng Liu
    • 2
  1. 1.Department of EECSUniversity of KansasUSA
  2. 2.College of ISTThe Pennsylvania State UniversityUSA

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