A taxonomy of privacy-preserving record linkage techniques
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TLDR
This paper presents an overview of techniques that allow the linking of databases between organizations while at the same time preserving the privacy of these data, and presents a taxonomy of PPRL techniques to characterize these techniques along 15 dimensions.About:
This article is published in Information Systems.The article was published on 2013-09-01 and is currently open access. It has received 241 citations till now. The article focuses on the topics: Record linkage & Data warehouse.read more
Figures
![Fig. 6. k-Anonymized records (k¼2) as used by Kantarcioglu et al. [108], Inan et al. [74], and Mohammed et al. [109].](/figures/fig-6-k-anonymized-records-k1-42-as-used-by-kantarcioglu-et-3vvb28qp.png)
Fig. 6. k-Anonymized records (k¼2) as used by Kantarcioglu et al. [108], Inan et al. [74], and Mohammed et al. [109]. ![Fig. 7. Bloom filter mapping as used by Schnell et al. [114], Karakasidis et al. [115], and Durham et al. [113,128].](/figures/fig-7-bloom-filter-mapping-as-used-by-schnell-et-al-114-wupq6nrg.png)
Fig. 7. Bloom filter mapping as used by Schnell et al. [114], Karakasidis et al. [115], and Durham et al. [113,128]. ![Fig. 4. Secure hash encoding for exact matching as used by Van Eycken et al. [126], Weber et al. [76], and Quantin et al. [86–89].](/figures/fig-4-secure-hash-encoding-for-exact-matching-as-used-by-van-261mhm7c.png)
Fig. 4. Secure hash encoding for exact matching as used by Van Eycken et al. [126], Weber et al. [76], and Quantin et al. [86–89]. ![Fig. 5. Multi-party private record matching using Bloom filters as proposed by Lai et al. [116].](/figures/fig-5-multi-party-private-record-matching-using-bloom-2los1a7m.png)
Fig. 5. Multi-party private record matching using Bloom filters as proposed by Lai et al. [116]. 
Fig. 1. Outline of the general record linkage proces ![Fig. 13. k-Anonymous phonetic encoding (k¼3) as proposed by Karakasidis et al. [101].](/figures/fig-13-k-anonymous-phonetic-encoding-k1-43-as-proposed-by-1zkl5ej5.png)
Fig. 13. k-Anonymous phonetic encoding (k¼3) as proposed by Karakasidis et al. [101].
![Fig. 6. k-Anonymized records (k¼2) as used by Kantarcioglu et al. [108], Inan et al. [74], and Mohammed et al. [109].](/figures/fig-6-k-anonymized-records-k1-42-as-used-by-kantarcioglu-et-3vvb28qp.webp)
![Fig. 7. Bloom filter mapping as used by Schnell et al. [114], Karakasidis et al. [115], and Durham et al. [113,128].](/figures/fig-7-bloom-filter-mapping-as-used-by-schnell-et-al-114-wupq6nrg.webp)
![Fig. 4. Secure hash encoding for exact matching as used by Van Eycken et al. [126], Weber et al. [76], and Quantin et al. [86–89].](/figures/fig-4-secure-hash-encoding-for-exact-matching-as-used-by-van-261mhm7c.webp)
![Fig. 5. Multi-party private record matching using Bloom filters as proposed by Lai et al. [116].](/figures/fig-5-multi-party-private-record-matching-using-bloom-2los1a7m.webp)
![Fig. 13. k-Anonymous phonetic encoding (k¼3) as proposed by Karakasidis et al. [101].](/figures/fig-13-k-anonymous-phonetic-encoding-k1-43-as-proposed-by-1zkl5ej5.webp)
Citations
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Journal ArticleDOI
A fast privacy-preserving patient record linkage of time series data
TL;DR: In this article , a fast and reliable record linkage algorithm was proposed to accurately match patient records in the original and subset databases while maintaining privacy, and a privacy preserving framework was introduced to enable health institutions to safely release their raw time series records to researchers with bare minimum amount of identifying information.
Journal ArticleDOI
Privacy-preserving record linkage using autoencoders
TL;DR: In this paper , the authors proposed a method based on autoencoders that transforms Bloom Filters into vectors of real numbers to achieve a high comparison quality of the generated numerical vectors and guarantee the comparability of encodings generated by different data owners.
Book ChapterDOI
An Overview of Big Data Issues in Privacy-Preserving Record Linkage
TL;DR: This paper proposes an analysis tool for the computational aspects of PPRL, and characterize existing P PRL techniques along five dimensions, and identifies research gaps in current literature and promising directions for future work.
Posted Content
Accurate and Efficient Suffix Tree Based Privacy-Preserving String Matching.
TL;DR: In this article, the authors proposed a novel approach for accurate and efficient privacy-preserving string matching based on suffix trees that are encoded using chained hashing and incorporated a hashing based encoding technique upon the encoded suffixes to improve privacy against frequency attacks such as those exploiting Benford's law.
Book ChapterDOI
Record Linkage als zentraler Baustein der Forschung mit Registern und Big Data-Nutzungen
TL;DR: In untechnischen Veroffentlichungen wird gelegentlich der Begriff „fuzzy matching“ verwendet, wobei dieser keine feste Bedeutung besitzt as mentioned in this paper.
References
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