TY - GEN
T1 - Privacy preserving group linkage
AU - Li, Fengjun
AU - Chen, Yuxin
AU - Luo, Bo
AU - Lee, Dongwon
AU - Liu, Peng
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=79961178919&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79961178919&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-22351-8_27
DO - 10.1007/978-3-642-22351-8_27
M3 - Conference contribution
AN - SCOPUS:79961178919
SN - 9783642223501
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 432
EP - 450
BT - Scientific and Statistical Database Management - 23rd International Conference, SSDBM 2011, Proceedings
T2 - 23rd International Conference on Scientific and Statistical Database Management, SSDBM 2011
Y2 - 20 July 2011 through 22 July 2011
ER -