Space/time trade-offs in hash coding with allowable errors
Communications of the ACM
Similarity Search in High Dimensions via Hashing
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Tools for privacy preserving distributed data mining
ACM SIGKDD Explorations Newsletter
Information sharing across private databases
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Practical Techniques for Searches on Encrypted Data
SP '00 Proceedings of the 2000 IEEE Symposium on Security and Privacy
On the Privacy Preserving Properties of Random Data Perturbation Techniques
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Foundations of Cryptography: Volume 2, Basic Applications
Foundations of Cryptography: Volume 2, Basic Applications
Secure and private sequence comparisons
Proceedings of the 2003 ACM workshop on Privacy in the electronic society
Privacy-preserving data integration and sharing
Proceedings of the 9th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
Privacy-preserving data linkage protocols
Proceedings of the 2004 ACM workshop on Privacy in the electronic society
Privacy preserving schema and data matching
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Privacy-Preserving Data Linkage and Geocoding: Current Approaches and Research Directions
ICDMW '06 Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops
A Privacy-Preserving Framework for Integrating Person-Specific Databases
PSD '08 Proceedings of the UNESCO Chair in data privacy international conference on Privacy in Statistical Databases
Privacy-Preserving String Comparisons in Record Linkage Systems: A Review
Information Security Journal: A Global Perspective
A Hybrid Approach to Private Record Linkage
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Geocode Matching and Privacy Preservation
Privacy, Security, and Trust in KDD
Private record matching using differential privacy
Proceedings of the 13th International Conference on Extending Database Technology
Privacy-preserving record linkage
PSD'10 Proceedings of the 2010 international conference on Privacy in statistical databases
A constraint satisfaction cryptanalysis of bloom filters in private record linkage
PETS'11 Proceedings of the 11th international conference on Privacy enhancing technologies
Anonymity meets game theory: secure data integration with malicious participants
The VLDB Journal — The International Journal on Very Large Data Bases
Keyword search and oblivious pseudorandom functions
TCC'05 Proceedings of the Second international conference on Theory of Cryptography
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)
A Survey of Indexing Techniques for Scalable Record Linkage and Deduplication
IEEE Transactions on Knowledge and Data Engineering
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
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Record linkage is the process of identifying which records in different databases refer to the same real-world entities. When personal details of individuals, such as names and addresses, are used to link databases across different organisations, then privacy becomes a major concern. Often it is not permissible to exchange identifying data among organisations. Linking databases in situations where no private or confidential information can be revealed is known as 'privacy-preserving record linkage' (PPRL). We propose a novel protocol for scalable and approximate PPRL based on Bloom filters in a scenario where no third party is available to conduct a linkage. While two-party protocols are more secure because there is no possibility of collusion between one of the database owners and the third party, these protocols generally require more complex and expensive techniques to ensure that a database owner cannot infer any sensitive information about the other party's data during the linkage process. Our two-party protocol uses an efficient privacy technique called Bloom filters, and conducts an iterative classification of record pairs into matches and non-matches, as selected bits of the Bloom filters are revealed. Experiments conducted on real-world databases that contain nearly two million records, show that our protocol is scalable to large databases while providing sufficient privacy characteristics and achieving high linkage quality.