TY - JOUR
T1 - Secure distributed computation of anonymized views of shared databases
AU - Tassa, Tamir
AU - Gudes, Ehud
N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2012/5
Y1 - 2012/5
N2 - We consider the problem of computing efficient anonymizations of partitioned databases. Given a database that is partitioned between several sites, either horizontally or vertically, we devise secure distributed algorithms that allow the different sites to obtain a k-anonymized and £-diverse view of the union of their databases, without disclosing sensitive information. Our algorithms are based on the sequential algorithm [Goldberger and Tassa 2010] that offers anonymizations with utility that is significantly better than other anonymization algorithms, and in particular those that were implemented so far in the distributed setting. Our algorithms can apply to different generalization techniques and utility measures and to any number of sites. While previous distributed algorithms depend on costly cryptographic primitives, the cryptographic assumptions of our solution are surprisingly minimal.
AB - We consider the problem of computing efficient anonymizations of partitioned databases. Given a database that is partitioned between several sites, either horizontally or vertically, we devise secure distributed algorithms that allow the different sites to obtain a k-anonymized and £-diverse view of the union of their databases, without disclosing sensitive information. Our algorithms are based on the sequential algorithm [Goldberger and Tassa 2010] that offers anonymizations with utility that is significantly better than other anonymization algorithms, and in particular those that were implemented so far in the distributed setting. Our algorithms can apply to different generalization techniques and utility measures and to any number of sites. While previous distributed algorithms depend on costly cryptographic primitives, the cryptographic assumptions of our solution are surprisingly minimal.
KW - Distributed data mining
KW - K-anonymization
KW - Privacy-preserving data mining
KW - Secure multiparty computation
UR - http://www.scopus.com/inward/record.url?scp=84863607195&partnerID=8YFLogxK
U2 - 10.1145/2188349.2188353
DO - 10.1145/2188349.2188353
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AN - SCOPUS:84863607195
SN - 0362-5915
VL - 37
JO - ACM Transactions on Database Systems
JF - ACM Transactions on Database Systems
IS - 2
M1 - 11
ER -