Cryptographically Secure Private Record Linkage Using Locality-Sensitive Hashing

Summary: Introduces cryptographically secure two-party private record linkage using locality-sensitive hashing, avoiding differential-privacy leakage and difficult locality-preserving hashes. Oblivious algorithms enable scalable blocking, achieving 99.3–99.9% accuracy and >10× speedups on 40K-record datasets. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID: 13942
Venue: VLDB
Year: 2024
Pagerank: 5.3766157e-05
Overall Rank: 8,732 | 40.10%
DOI: 10.14778/3626292.3626293

Incoming Non-self Citations Over Time

Authors

1. Ruidi Wei (University of Waterloo)
2. Florian Kerschbaum (University of Waterloo)

BibTeX Citation

@article{wei_vldb24,
        title = {{Cryptographically Secure Private Record Linkage Using Locality-Sensitive Hashing}},
        author = {Wei, Ruidi and Kerschbaum, Florian},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {2},
        pages = {79--91},
        doi = {10.14778/3626292.3626293},
        url = {https://doi.org/10.14778/3626292.3626293},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,921	Sectric: Towards Accurate, Privacy-preserving and Efficient Triangle Counting	2025	VLDB	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
248	Evaluation of entity resolution approaches on real-world match problems	2010	VLDB	0.00023278354
2,045	Efficient Oblivious Database Joins	2020	VLDB	9.2632279e-05

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