MERLIN - A tool for multi-party privacy-preserving record linkage

Thilina Ranbaduge; Dinusha Vatsalan; Peter Christen

doi:10.1109/ICDMW.2015.101

MERLIN - A tool for multi-party privacy-preserving record linkage

Thilina Ranbaduge, Dinusha Vatsalan, Peter Christen

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

3 Citations (Scopus)

Abstract

Many organizations, including businesses, government agencies and research organizations, are collecting vast amounts of data, which are stored, processed and analyzed to mine interesting patterns and knowledge to support efficient and quality decision making. In order to improve data quality and to facilitate further analysis, many application domains require information from multiple sources to be integrated and combined. The process of matching and aggregating records that relate to the same entities from different data sources without compromising their privacy is known as 'privacy-preserving record linkage' (PPRL), 'blind data linkage' or 'private record linkage'. In this paper we present MERLIN, an online tool that demonstrates various PPRL methods in a multi-party context. In this demonstration we show different private multi-party blocking and matching techniques, and illustrate the usability of MERLIN by presenting quality and performance measures of various PPRL methods. We believe MERLIN will help practitioners and researchers to better understand the pipeline of the PPRL process, to compare different multi-party PPRL techniques, and to determine the best technique to use for their needs.

Original language	English
Title of host publication	Proceedings - 15th IEEE International Conference on Data Mining Workshop
Editors	Peng Cui, Jennifer Dy, Charu Aggarwal, Zhi-Hua Zhou, Alexander Tuzhilin, Hui Xiong, Xindong Wu
Place of Publication	Piscataway, NJ
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	1640-1643
Number of pages	4
ISBN (Electronic)	9781467384926
DOIs	https://doi.org/10.1109/ICDMW.2015.101
Publication status	Published - 2015
Externally published	Yes
Event	15th IEEE International Conference on Data Mining Workshop, ICDMW 2015 - Atlantic City, United States Duration: 14 Nov 2015 → 17 Nov 2015

Other

Other	15th IEEE International Conference on Data Mining Workshop, ICDMW 2015
Country/Territory	United States
City	Atlantic City
Period	14/11/15 → 17/11/15

Keywords

Privacy
data matching
Bloom filters
scalability
online demo

Access to Document

10.1109/ICDMW.2015.101

Cite this

Ranbaduge, T., Vatsalan, D., & Christen, P. (2015). MERLIN - A tool for multi-party privacy-preserving record linkage. In P. Cui, J. Dy, C. Aggarwal, Z.-H. Zhou, A. Tuzhilin, H. Xiong, & X. Wu (Eds.), Proceedings - 15th IEEE International Conference on Data Mining Workshop (pp. 1640-1643). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICDMW.2015.101

Ranbaduge, Thilina ; Vatsalan, Dinusha ; Christen, Peter. / MERLIN - A tool for multi-party privacy-preserving record linkage. Proceedings - 15th IEEE International Conference on Data Mining Workshop . editor / Peng Cui ; Jennifer Dy ; Charu Aggarwal ; Zhi-Hua Zhou ; Alexander Tuzhilin ; Hui Xiong ; Xindong Wu. Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2015. pp. 1640-1643

@inproceedings{6f6b4ad1360f4709b6f49e756231db87,

title = "MERLIN - A tool for multi-party privacy-preserving record linkage",

abstract = "Many organizations, including businesses, government agencies and research organizations, are collecting vast amounts of data, which are stored, processed and analyzed to mine interesting patterns and knowledge to support efficient and quality decision making. In order to improve data quality and to facilitate further analysis, many application domains require information from multiple sources to be integrated and combined. The process of matching and aggregating records that relate to the same entities from different data sources without compromising their privacy is known as 'privacy-preserving record linkage' (PPRL), 'blind data linkage' or 'private record linkage'. In this paper we present MERLIN, an online tool that demonstrates various PPRL methods in a multi-party context. In this demonstration we show different private multi-party blocking and matching techniques, and illustrate the usability of MERLIN by presenting quality and performance measures of various PPRL methods. We believe MERLIN will help practitioners and researchers to better understand the pipeline of the PPRL process, to compare different multi-party PPRL techniques, and to determine the best technique to use for their needs.",

keywords = "Privacy, data matching, Bloom filters, scalability, online demo",

author = "Thilina Ranbaduge and Dinusha Vatsalan and Peter Christen",

year = "2015",

doi = "10.1109/ICDMW.2015.101",

language = "English",

pages = "1640--1643",

editor = "Peng Cui and Jennifer Dy and Charu Aggarwal and Zhi-Hua Zhou and Alexander Tuzhilin and Hui Xiong and Xindong Wu",

booktitle = "Proceedings - 15th IEEE International Conference on Data Mining Workshop",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "15th IEEE International Conference on Data Mining Workshop, ICDMW 2015 ; Conference date: 14-11-2015 Through 17-11-2015",

}

Ranbaduge, T, Vatsalan, D & Christen, P 2015, MERLIN - A tool for multi-party privacy-preserving record linkage. in P Cui, J Dy, C Aggarwal, Z-H Zhou, A Tuzhilin, H Xiong & X Wu (eds), Proceedings - 15th IEEE International Conference on Data Mining Workshop . Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 1640-1643, 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015, Atlantic City, United States, 14/11/15. https://doi.org/10.1109/ICDMW.2015.101

MERLIN - A tool for multi-party privacy-preserving record linkage. / Ranbaduge, Thilina; Vatsalan, Dinusha; Christen, Peter.
Proceedings - 15th IEEE International Conference on Data Mining Workshop . ed. / Peng Cui; Jennifer Dy; Charu Aggarwal; Zhi-Hua Zhou; Alexander Tuzhilin; Hui Xiong; Xindong Wu. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2015. p. 1640-1643.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

TY - GEN

T1 - MERLIN - A tool for multi-party privacy-preserving record linkage

AU - Ranbaduge, Thilina

AU - Vatsalan, Dinusha

AU - Christen, Peter

PY - 2015

Y1 - 2015

N2 - Many organizations, including businesses, government agencies and research organizations, are collecting vast amounts of data, which are stored, processed and analyzed to mine interesting patterns and knowledge to support efficient and quality decision making. In order to improve data quality and to facilitate further analysis, many application domains require information from multiple sources to be integrated and combined. The process of matching and aggregating records that relate to the same entities from different data sources without compromising their privacy is known as 'privacy-preserving record linkage' (PPRL), 'blind data linkage' or 'private record linkage'. In this paper we present MERLIN, an online tool that demonstrates various PPRL methods in a multi-party context. In this demonstration we show different private multi-party blocking and matching techniques, and illustrate the usability of MERLIN by presenting quality and performance measures of various PPRL methods. We believe MERLIN will help practitioners and researchers to better understand the pipeline of the PPRL process, to compare different multi-party PPRL techniques, and to determine the best technique to use for their needs.

AB - Many organizations, including businesses, government agencies and research organizations, are collecting vast amounts of data, which are stored, processed and analyzed to mine interesting patterns and knowledge to support efficient and quality decision making. In order to improve data quality and to facilitate further analysis, many application domains require information from multiple sources to be integrated and combined. The process of matching and aggregating records that relate to the same entities from different data sources without compromising their privacy is known as 'privacy-preserving record linkage' (PPRL), 'blind data linkage' or 'private record linkage'. In this paper we present MERLIN, an online tool that demonstrates various PPRL methods in a multi-party context. In this demonstration we show different private multi-party blocking and matching techniques, and illustrate the usability of MERLIN by presenting quality and performance measures of various PPRL methods. We believe MERLIN will help practitioners and researchers to better understand the pipeline of the PPRL process, to compare different multi-party PPRL techniques, and to determine the best technique to use for their needs.

KW - Privacy

KW - data matching

KW - Bloom filters

KW - scalability

KW - online demo

UR - https://dataportal.arc.gov.au/NCGP/Web/Grant/Grant/DP130101801

U2 - 10.1109/ICDMW.2015.101

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M3 - Conference proceeding contribution

SP - 1640

EP - 1643

BT - Proceedings - 15th IEEE International Conference on Data Mining Workshop

A2 - Cui, Peng

A2 - Dy, Jennifer

A2 - Aggarwal, Charu

A2 - Zhou, Zhi-Hua

A2 - Tuzhilin, Alexander

A2 - Xiong, Hui

A2 - Wu, Xindong

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Piscataway, NJ

T2 - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015

Y2 - 14 November 2015 through 17 November 2015

ER -

Ranbaduge T, Vatsalan D, Christen P. MERLIN - A tool for multi-party privacy-preserving record linkage. In Cui P, Dy J, Aggarwal C, Zhou ZH, Tuzhilin A, Xiong H, Wu X, editors, Proceedings - 15th IEEE International Conference on Data Mining Workshop . Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). 2015. p. 1640-1643 doi: 10.1109/ICDMW.2015.101

MERLIN - A tool for multi-party privacy-preserving record linkage

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