The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Privacy-preserving data mining
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Enhancing privacy and trust in electronic communities
Proceedings of the 1st ACM conference on Electronic commerce
Tools for privacy preserving distributed data mining
ACM SIGKDD Explorations Newsletter
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Information sharing across private databases
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
TAILOR: A Record Linkage Tool Box
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Foundations of Cryptography: Volume 2, Basic Applications
Foundations of Cryptography: Volume 2, Basic Applications
Blocking-aware private record linkage
Proceedings of the 2nd international workshop on Information quality in information systems
Mondrian Multidimensional K-Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
\ell -Diversity: Privacy Beyond \kappa -Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Privacy Preserving Query Processing Using Third Parties
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Duplicate Record Detection: A Survey
IEEE Transactions on Knowledge and Data Engineering
Secure set intersection cardinality with application to association rule mining
Journal of Computer Security
Privacy preserving schema and data matching
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Output perturbation with query relaxation
Proceedings of the VLDB Endowment
A Hybrid Approach to Private Record Linkage
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
ICALP'06 Proceedings of the 33rd international conference on Automata, Languages and Programming - Volume Part II
Privacy-preserving set operations
CRYPTO'05 Proceedings of the 25th annual international conference on Advances in Cryptology
Calibrating noise to sensitivity in private data analysis
TCC'06 Proceedings of the Third conference on Theory of Cryptography
A Cryptographic Approach to Securely Share and Query Genomic Sequences
IEEE Transactions on Information Technology in Biomedicine
Differentially private data release through multidimensional partitioning
SDM'10 Proceedings of the 7th VLDB conference on Secure data management
Differentially private data release for data mining
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Privacy preserving group linkage
SSDBM'11 Proceedings of the 23rd international conference on Scientific and statistical database management
Anonymity meets game theory: secure data integration with malicious participants
The VLDB Journal — The International Journal on Very Large Data Bases
Fake injection strategies for private phonetic matching
DPM'11 Proceedings of the 6th international conference, and 4th international conference on Data Privacy Management and Autonomous Spontaneus Security
Reference table based k-anonymous private blocking
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Efficient and Practical Approach for Private Record Linkage
Journal of Data and Information Quality (JDIQ)
The application of differential privacy to health data
Proceedings of the 2012 Joint EDBT/ICDT Workshops
PrivBasis: frequent itemset mining with differential privacy
Proceedings of the VLDB Endowment
Frequent grams based embedding for privacy preserving record linkage
Proceedings of the 21st ACM international conference on Information and knowledge management
Non-interactive differential privacy: a survey
Proceedings of the First International Workshop on Open Data
Efficient privacy-aware record integration
Proceedings of the 16th International Conference on Extending Database Technology
Efficient and accurate strategies for differentially-private sliding window queries
Proceedings of the 16th International Conference on Extending Database Technology
A privacy framework: indistinguishable privacy
Proceedings of the Joint EDBT/ICDT 2013 Workshops
LinkIT: privacy preserving record linkage and integration via transformations
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
PrivGene: differentially private model fitting using genetic algorithms
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
A taxonomy of privacy-preserving record linkage techniques
Information Systems
An efficient two-party protocol for approximate matching in private record linkage
AusDM '11 Proceedings of the Ninth Australasian Data Mining Conference - Volume 121
Efficient two-party private blocking based on sorted nearest neighborhood clustering
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
An iterative two-party protocol for scalable privacy-preserving record linkage
AusDM '12 Proceedings of the Tenth Australasian Data Mining Conference - Volume 134
Mining frequent patterns with differential privacy
Proceedings of the VLDB Endowment
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Private matching between datasets owned by distinct parties is a challenging problem with several applications. Private matching allows two parties to identify the records that are close to each other according to some distance functions, such that no additional information other than the join result is disclosed to any party. Private matching can be solved securely and accurately using secure multi-party computation (SMC) techniques, but such an approach is prohibitively expensive in practice. Previous work proposed the release of sanitized versions of the sensitive datasets which allows blocking, i.e., filtering out sub-sets of records that cannot be part of the join result. This way, SMC is applied only to a small fraction of record pairs, reducing the matching cost to acceptable levels. The blocking step is essential for the privacy, accuracy and efficiency of matching. However, the state-of-the-art focuses on sanitization based on k-anonymity, which does not provide sufficient privacy. We propose an alternative design centered on differential privacy, a novel paradigm that provides strong privacy guarantees. The realization of the new model presents difficult challenges, such as the evaluation of distance-based matching conditions with the help of only a statistical queries interface. Specialized versions of data indexing structures (e.g., kd-trees) also need to be devised, in order to comply with differential privacy. Experiments conducted on the real-world Census-income dataset show that, although our methods provide strong privacy, their effectiveness in reducing matching cost is not far from that of k-anonymity based counterparts.