Enabling analytics on sensitive medical data with secure multi-party computation

Meilof Veeningen; Supriyo Chatterjea; Anna Zsófia Horváth; Gerald Spindler; Eric Boersma; Peter van der Spek; Onno van der Galiën; Job Gutteling; Wessel Kraaij; Thijs Veugen

doi:10.3233/978-1-61499-852-5-76

Enabling analytics on sensitive medical data with secure multi-party computation

Meilof Veeningen^*, Supriyo Chatterjea, Anna Zsófia Horváth, Gerald Spindler, Eric Boersma, Peter van der Spek, Onno van der Galiën, Job Gutteling, Wessel Kraaij, Thijs Veugen

^*Corresponding author for this work

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

12 Citations (Scopus)

8 Downloads (Pure)

Abstract

While there is a clear need to apply data analytics in the healthcare sector, this is often difficult because it requires combining sensitive data from multiple data sources. In this paper, we show how the cryptographic technique of secure multiparty computation can enable such data analytics by performing analytics without the need to share the underlying data. We discuss the issue of compliance to European privacy legislation; report on three pilots bringing these techniques closer to practice; and discuss the main challenges ahead to make fully privacy-preserving data analytics in the medical sector commonplace.

Original language	English
Title of host publication	Building Continents of Knowledge in Oceans of Data
Subtitle of host publication	The Future of Co-Created eHealth - Proceedings of MIE 2018
Editors	Adrien Ugon, Daniel Karlsson, Gunnar O. Klein, Anne Moen
Publisher	IOS
Pages	76-80
Number of pages	5
ISBN (Electronic)	9781614998518
DOIs	https://doi.org/10.3233/978-1-61499-852-5-76
Publication status	Published - 2018
Externally published	Yes
Event	40th Medical Informatics in Europe Conference, MIE 2018 - Gothenburg, Sweden Duration: 24 Apr 2018 → 26 Apr 2018 Conference number: 40

Publication series

Name	Studies in Health Technology and Informatics
Publisher	IOS Press
Volume	247
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Conference

Conference	40th Medical Informatics in Europe Conference, MIE 2018
Abbreviated title	MIE 2018
Country/Territory	Sweden
City	Gothenburg
Period	24/04/18 → 26/04/18

Keywords

Big data
Data sharing
General data protection regulation
Privacy
Privacy-preserving data mining
Secure multi-party computation
n/a OA procedure

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10.3233/978-1-61499-852-5-76Licence: CC BY-NC

ArticleFinal published version, 187 KBLicence: CC BY-NC

Cite this

Veeningen, M., Chatterjea, S., Horváth, A. Z., Spindler, G., Boersma, E., van der Spek, P., van der Galiën, O., Gutteling, J., Kraaij, W., & Veugen, T. (2018). Enabling analytics on sensitive medical data with secure multi-party computation. In A. Ugon, D. Karlsson, G. O. Klein, & A. Moen (Eds.), Building Continents of Knowledge in Oceans of Data: The Future of Co-Created eHealth - Proceedings of MIE 2018 (pp. 76-80). (Studies in Health Technology and Informatics; Vol. 247). IOS. https://doi.org/10.3233/978-1-61499-852-5-76

Veeningen, Meilof ; Chatterjea, Supriyo ; Horváth, Anna Zsófia et al. / Enabling analytics on sensitive medical data with secure multi-party computation. Building Continents of Knowledge in Oceans of Data: The Future of Co-Created eHealth - Proceedings of MIE 2018. editor / Adrien Ugon ; Daniel Karlsson ; Gunnar O. Klein ; Anne Moen. IOS, 2018. pp. 76-80 (Studies in Health Technology and Informatics).

@inproceedings{5381315fa7ca48a1a6311ea77ad4f654,

title = "Enabling analytics on sensitive medical data with secure multi-party computation",

abstract = "While there is a clear need to apply data analytics in the healthcare sector, this is often difficult because it requires combining sensitive data from multiple data sources. In this paper, we show how the cryptographic technique of secure multiparty computation can enable such data analytics by performing analytics without the need to share the underlying data. We discuss the issue of compliance to European privacy legislation; report on three pilots bringing these techniques closer to practice; and discuss the main challenges ahead to make fully privacy-preserving data analytics in the medical sector commonplace.",

keywords = "Big data, Data sharing, General data protection regulation, Privacy, Privacy-preserving data mining, Secure multi-party computation, n/a OA procedure",

author = "Meilof Veeningen and Supriyo Chatterjea and Horv{\'a}th, {Anna Zs{\'o}fia} and Gerald Spindler and Eric Boersma and {van der Spek}, Peter and {van der Gali{\"e}n}, Onno and Job Gutteling and Wessel Kraaij and Thijs Veugen",

note = "Funding Information: Acknowledgements. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 731583 and 780495 and is co-financed from a PPS allowance for research and innovation from the Dutch Ministry of Economic affairs. Publisher Copyright: {\textcopyright} 2018 European Federation for Medical Informatics (EFMI) and IOS Press.; 40th Medical Informatics in Europe Conference, MIE 2018, MIE 2018 ; Conference date: 24-04-2018 Through 26-04-2018",

year = "2018",

doi = "10.3233/978-1-61499-852-5-76",

language = "English",

series = "Studies in Health Technology and Informatics",

publisher = "IOS",

pages = "76--80",

editor = "Adrien Ugon and Daniel Karlsson and Klein, {Gunnar O.} and Anne Moen",

booktitle = "Building Continents of Knowledge in Oceans of Data",

address = "Netherlands",

}

Veeningen, M, Chatterjea, S, Horváth, AZ, Spindler, G, Boersma, E, van der Spek, P, van der Galiën, O, Gutteling, J, Kraaij, W & Veugen, T 2018, Enabling analytics on sensitive medical data with secure multi-party computation. in A Ugon, D Karlsson, GO Klein & A Moen (eds), Building Continents of Knowledge in Oceans of Data: The Future of Co-Created eHealth - Proceedings of MIE 2018. Studies in Health Technology and Informatics, vol. 247, IOS, pp. 76-80, 40th Medical Informatics in Europe Conference, MIE 2018, Gothenburg, Sweden, 24/04/18. https://doi.org/10.3233/978-1-61499-852-5-76

Enabling analytics on sensitive medical data with secure multi-party computation. / Veeningen, Meilof; Chatterjea, Supriyo; Horváth, Anna Zsófia et al.
Building Continents of Knowledge in Oceans of Data: The Future of Co-Created eHealth - Proceedings of MIE 2018. ed. / Adrien Ugon; Daniel Karlsson; Gunnar O. Klein; Anne Moen. IOS, 2018. p. 76-80 (Studies in Health Technology and Informatics; Vol. 247).

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

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T1 - Enabling analytics on sensitive medical data with secure multi-party computation

AU - Veeningen, Meilof

AU - Chatterjea, Supriyo

AU - Horváth, Anna Zsófia

AU - Spindler, Gerald

AU - Boersma, Eric

AU - van der Spek, Peter

AU - van der Galiën, Onno

AU - Gutteling, Job

AU - Kraaij, Wessel

AU - Veugen, Thijs

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N2 - While there is a clear need to apply data analytics in the healthcare sector, this is often difficult because it requires combining sensitive data from multiple data sources. In this paper, we show how the cryptographic technique of secure multiparty computation can enable such data analytics by performing analytics without the need to share the underlying data. We discuss the issue of compliance to European privacy legislation; report on three pilots bringing these techniques closer to practice; and discuss the main challenges ahead to make fully privacy-preserving data analytics in the medical sector commonplace.

AB - While there is a clear need to apply data analytics in the healthcare sector, this is often difficult because it requires combining sensitive data from multiple data sources. In this paper, we show how the cryptographic technique of secure multiparty computation can enable such data analytics by performing analytics without the need to share the underlying data. We discuss the issue of compliance to European privacy legislation; report on three pilots bringing these techniques closer to practice; and discuss the main challenges ahead to make fully privacy-preserving data analytics in the medical sector commonplace.

KW - Big data

KW - Data sharing

KW - General data protection regulation

KW - Privacy

KW - Privacy-preserving data mining

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BT - Building Continents of Knowledge in Oceans of Data

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A2 - Karlsson, Daniel

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ER -

Veeningen M, Chatterjea S, Horváth AZ, Spindler G, Boersma E, van der Spek P et al. Enabling analytics on sensitive medical data with secure multi-party computation. In Ugon A, Karlsson D, Klein GO, Moen A, editors, Building Continents of Knowledge in Oceans of Data: The Future of Co-Created eHealth - Proceedings of MIE 2018. IOS. 2018. p. 76-80. (Studies in Health Technology and Informatics). doi: 10.3233/978-1-61499-852-5-76

Enabling analytics on sensitive medical data with secure multi-party computation

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Keywords

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