Journal ArticleDOI
Secure Approximate String Matching for Privacy-Preserving Record Linkage
TLDR
This work presents a novel public-key construction for secure two-party evaluation of threshold functions in restricted domains based on embeddings found in the message spaces of additively homomorphic encryption schemes.Abstract:
Real-world applications of record linkage often require matching to be robust in spite of small variations in string fields. For example, two health care providers should be able to detect a patient in common, even if one record contains a typo or transcription error. In the privacy-preserving setting, however, the problem of approximate string matching has been cast as a trade-off between security and practicality, and the literature has mainly focused on Bloom filter encodings , an approach which can leak significant information about the underlying records. We present a novel public-key construction for secure two-party evaluation of threshold functions in restricted domains based on embeddings found in the message spaces of additively homomorphic encryption schemes. We use this to construct an efficient two-party protocol for privately computing the threshold Dice coefficient. Relative to the approach of Bloom filter encodings, our proposal offers formal security guarantees and greater matching accuracy. We implement the protocol and demonstrate the feasibility of this approach in linking medium-sized patient databases with tens of thousands of records.read more
Citations
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Proceedings ArticleDOI
A two-party private string matching fuzzy vault scheme
TL;DR: In this paper, a two-party privacy-preserving approximate string matching methodology based on a novel Fuzzy Vault scheme was proposed, which combines the approximation and security properties of fuzzy vaults for record linkage purposes.
Journal ArticleDOI
Accurate and efficient privacy-preserving string matching
TL;DR: In this article , the authors proposed two new approaches for accurate and efficient privacy-preserving string matching that provide privacy against various attacks, and evaluated their approaches on several data sets with different types of strings, and validate their privacy, accuracy, and complexity compared to three baseline techniques, showing that they outperform all baselines.
Proceedings ArticleDOI
Encrypted video search: scalable, modular, and content-similar
TL;DR: This work begins the study of scalable encrypted video search in which a client can search videos similar to an image query, and advocates two-step searches by incorporating lightweight searchable encryption techniques for pre-screening and an interactive approach for fine-grained search.
Journal ArticleDOI
An Improved Chinese String Comparator for Bloom Filter Based Privacy-Preserving Record Linkage
TL;DR: Wang et al. as discussed by the authors proposed a method for PPRL in Chinese language environment, where Chinese characters (identification fields in record pairs) are encoded into strings composed of letters and numbers by using the SoundShape code according to their shapes and pronunciations.
Book ChapterDOI
Privacy-preserving record linkage using local sensitive hash and private set intersection
TL;DR: In this article , the authors proposed a new and efficient privacy-preserving record linkage (PPRL) protocol that combines PSI and local sensitive hash (LSH) functions, and runs in linear time.
References
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Book ChapterDOI
Efficient Private Matching and Set Intersection
TL;DR: In this paper, the problem of computing the intersection of private datasets of two parties, where the datasets contain lists of elements taken from a large domain, was considered and protocols based on the use of homomorphic encryption and balanced hashing were proposed.
Efficient private matching and set intersection
TL;DR: This work considers the problem of computing the intersection of private datasets of two parties, where the datasets contain lists of elements taken from a large domain, and presents protocols, based on the use of homomorphic encryption and balanced hashing, for both semi-honest and malicious environments.
Proceedings ArticleDOI
When private set intersection meets big data: an efficient and scalable protocol
TL;DR: A new Private Set Intersection (PSI) protocol that is extremely efficient and highly scalable compared with existing protocols, based on a novel approach that is oblivious Bloom intersection, which has linear complexity and relies mostly on efficient symmetric key operations.
Proceedings ArticleDOI
Privacy-preserving multi-keyword fuzzy search over encrypted data in the cloud
TL;DR: This paper proposes a novel multi-keyword fuzzy search scheme that achieves fuzzy matching through algorithmic design rather than expanding the index file and effectively supports multiple keyword fuzzy search without increasing the index or search complexity.