Randomized Response and Balanced Bloom Filters for Privacy Preserving Record Linkage
MetadataShow full item record
© 2016 IEEE. In most European settings, record linkage across different institutions is based on encrypted personal identifiers-such as names, birthdays, or places of birth-To protect privacy. However, in practice up to 20% of the records may contain errors in identifiers. Thus, exact record linkage on encrypted identifiers usually results in the loss of large subsets of the data. Such losses usually imply biased statistical estimates since the causes of errors might be correlated with the variables of interest in many applications. Over the past 10 years, the field of Privacy Preserving Record Linkage (PPRL) has developed different techniques to link data without revealing the identity of the described entity. However, only few techniques are suitable for applied research with large data bases that include millions of records, which is typical for administrative or medical data bases. Bloom filters were found to be one successful technique for PPRL when large scale applications are concerned. Yet, Bloom filters have been subject to cryptographic attacks. Previous research has shown that the straight application of Bloom filters has a non-zero re-identification risk. We present new results on recently developed techniques defying all known attacks on PPRL Bloom filters. The computationally inexpensive algorithms modify personal identifiers by combining different cryptographic techniques. The paper demonstrates these new algorithms and demonstrates their performance concerning precision, recall, and re-identification risk on large data bases.
Showing items related by title, author, creator and subject.
Evaluating privacy-preserving record linkage using cryptographic long-term keys and multibit trees on large medical datasets.Brown, A.; Borgs, C.; Randall, Sean; Schnell, R. (2017)Background: Integrating medical data using databases from different sources by record linkage is a powerful technique increasingly used in medical research. Under many jurisdictions, unique personal identifiers needed for ...
Brown, A.; Randall, Sean; Ferrante, A.; Semmens, J.; Boyd, J. (2017)Background: Probabilistic record linkage is a process used to bring together person-based records from within the same dataset (de-duplication) or from disparate datasets using pairwise comparisons and matching probabilities. ...
Randall, Sean; Ferrante, Anna; Boyd, James; Bauer, J.; Semmens, James (2014)Record linkage typically involves the use of dedicated linkage units who are supplied with personally identifying information to determine individuals from within and across datasets. The personally identifying information ...