@inproceedings{932cd4221b88481abd2f08f86be6a69c,
title = "Efficient cryptanalysis of bloom filters for privacy-preserving record linkage",
abstract = "Privacy-preserving record linkage (PPRL) is the process of identifying records that represent the same entity across databases held by different organizations without revealing any sensitive information about these entities. A popular technique used in PPRL is Bloom filter encoding, which has shown to be an efficient and effective way to encode sensitive information into bit vectors while still enabling approximate matching of attribute values. However, the encoded values in Bloom filters are vulnerable to cryptanalysis attacks. Under specific conditions, these attacks are successful in that some frequent sensitive attribute values can be re-identified. In this paper we propose and evaluate on real databases a novel efficient attack on Bloom filters. Our approach is based on the construction principle of Bloom filters of hashing elements of sets into bit positions. The attack is independent of the encoding function and its parameters used, it can correctly re-identify sensitive attribute values even when various recently proposed hardening techniques have been applied, and it runs in a few seconds instead of hours.",
keywords = "Data linkage, Data matching, Entity resolution, Frequency analysis, Privacy, Re-identification",
author = "Peter Christen and Rainer Schnell and Dinusha Vatsalan and Thilina Ranbaduge",
note = "Publisher Copyright: {\textcopyright} 2017, Springer International Publishing AG.; 21st Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2017 ; Conference date: 23-05-2017 Through 26-05-2017",
year = "2017",
doi = "10.1007/978-3-319-57454-7_49",
language = "English",
isbn = "9783319574530",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "628--640",
editor = "Kyuseok Shim and Jae-Gil Lee and Longbing Cao and Xuemin Lin and Jinho Kim and Yang-Sae Moon",
booktitle = "Advances in Knowledge Discovery and Data Mining - 21st Pacific-Asia Conference, PAKDD 2017, Proceedings",
address = "Germany",
}