KRAKEN: A Privacy-Preserving Data Market for Authentic Data

Karl Koch; Stephan Krenn; Tilen Marc; Stefan More; Sebastian Ramacher

doi:10.1145/3565011.3569057

KRAKEN: A Privacy-Preserving Data Market for Authentic Data

Karl Koch, Stephan Krenn, Tilen Marc, Stefan More, Sebastian Ramacher^*

^*Korrespondierende/r Autor/-in für diese Arbeit

Institut für Angewandte Informationsverarbeitung und Kommunikationstechnologie (7050)

Publikation: Beitrag in Buch/Bericht/Konferenzband › Beitrag in einem Konferenzband › Begutachtung

Abstract

Data marketplaces are online platforms that provide a way for individuals to monetize their (personal) data. In traditional data marketplaces, the data is uploaded to the marketplace platform in plain-text. Since the broker has access to all data, such marketplaces are risk to the user's privacy.

We present a privacy-preserving marketplace that allows data owners to keep control over their data. We use secure multi-party computation to enable data consumers to evaluate expressive functions on a set of data. In our marketplace, the broker has neither access to the data nor the results of a function evaluation. Furthermore, our design ensures data-origin authenticity and enables data owners to define data usage policies that are enforced by the computation nodes.

In addition to the architecture of this private marketplace, we discuss a reference implementation. We also provide an evaluation of our approach, demonstrating that its practicability.

Originalsprache	englisch
Titel	DE 2022 - Proceedings of the 1st International Workshop on Data Economy, Part of CoNEXT 2022
Untertitel	The First ACM Data Economy Workshop
Erscheinungsort	New York, NY
Herausgeber (Verlag)	Association of Computing Machinery
Seiten	15-20
Seitenumfang	6
ISBN (elektronisch)	978-1-4503-9923-4
DOIs	https://doi.org/10.1145/3565011.3569057
Publikationsstatus	Veröffentlicht - 9 Dez. 2022
Veranstaltung	2022 International Conference on Emerging Networking Experiments and Technologies: CoNEXT 2022 - Rom, Italien Dauer: 6 Dez. 2022 → 9 Dez. 2022 Konferenznummer: 2022 https://conferences2.sigcomm.org/co-next/2022

Publikationsreihe

Name	DE 2022 - Proceedings of the 1st International Workshop on Data Economy, Part of CoNEXT 2022

Konferenz

Konferenz	2022 International Conference on Emerging Networking Experiments and Technologies
Kurztitel	CoNEXT 2022
Land/Gebiet	Italien
Ort	Rom
Zeitraum	6/12/22 → 9/12/22
Internetadresse	https://conferences2.sigcomm.org/co-next/2022

ASJC Scopus subject areas

Informatik (sonstige)
Angewandte Informatik
Hardware und Architektur
Computernetzwerke und -kommunikation

Zugriff auf Dokument

10.1145/3565011.3569057Lizenz: CC BY 4.0

Andere Dateien und Links

Verknüpfung zur Publikation in Scopus

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1 Laufend

A-SIT - Zentrum für sichere Informationstechnologie Austria
Stranacher, K., Dominikus, S., Leitold, H., Marsalek, A., Teufl, P., Bauer, W., Aigner, M. J., Rössler, T., Neuherz, E., Dietrich, K., Zefferer, T., Mangard, S., Payer, U., Orthacker, C., Lipp, P., Reiter, A., Knall, T., Bratko, H., Bonato, M., Suzic, B., Zwattendorfer, B., Kreuzhuber, S., Oswald, M. E., Tauber, A., Posch, R., Bratko, D., Feichtner, J., Ivkovic, M., Reimair, F., Wolkerstorfer, J. & Scheibelhofer, K.
21/05/99 → 6/08/20
Projekt: Arbeitsgebiet
EU - KRAKEN - Vermittlungs- und Marktplattform für personenbezogene Daten
Tauber, A.
1/12/19 → 30/11/22
Projekt: Forschungsprojekt

KRAKEN: A Privacy-Preserving Data Market for Authentic Data
Karl Koch (Redner/in) & Stefan Josef More (Beitragende/r)
9 Dez. 2022
Aktivität: Vortrag oder Präsentation › Vortrag bei Konferenz oder Fachtagung › Science to science

Dieses zitieren

Koch, K., Krenn, S., Marc, T., More, S., & Ramacher, S. (2022). KRAKEN: A Privacy-Preserving Data Market for Authentic Data. in DE 2022 - Proceedings of the 1st International Workshop on Data Economy, Part of CoNEXT 2022: The First ACM Data Economy Workshop (S. 15-20). (DE 2022 - Proceedings of the 1st International Workshop on Data Economy, Part of CoNEXT 2022). Association of Computing Machinery. https://doi.org/10.1145/3565011.3569057

KRAKEN: A Privacy-Preserving Data Market for Authentic Data. / Koch, Karl; Krenn, Stephan; Marc, Tilen et al.
DE 2022 - Proceedings of the 1st International Workshop on Data Economy, Part of CoNEXT 2022: The First ACM Data Economy Workshop. New York, NY: Association of Computing Machinery, 2022. S. 15-20 (DE 2022 - Proceedings of the 1st International Workshop on Data Economy, Part of CoNEXT 2022).

Publikation: Beitrag in Buch/Bericht/Konferenzband › Beitrag in einem Konferenzband › Begutachtung

Koch, K, Krenn, S, Marc, T, More, S & Ramacher, S 2022, KRAKEN: A Privacy-Preserving Data Market for Authentic Data. in DE 2022 - Proceedings of the 1st International Workshop on Data Economy, Part of CoNEXT 2022: The First ACM Data Economy Workshop. DE 2022 - Proceedings of the 1st International Workshop on Data Economy, Part of CoNEXT 2022, Association of Computing Machinery, New York, NY, S. 15-20, 2022 International Conference on Emerging Networking Experiments and Technologies, Rom, Italien, 6/12/22. https://doi.org/10.1145/3565011.3569057

Koch K, Krenn S, Marc T, More S, Ramacher S. KRAKEN: A Privacy-Preserving Data Market for Authentic Data. in DE 2022 - Proceedings of the 1st International Workshop on Data Economy, Part of CoNEXT 2022: The First ACM Data Economy Workshop. New York, NY: Association of Computing Machinery. 2022. S. 15-20. (DE 2022 - Proceedings of the 1st International Workshop on Data Economy, Part of CoNEXT 2022). doi: 10.1145/3565011.3569057

Koch, Karl ; Krenn, Stephan ; Marc, Tilen et al. / KRAKEN: A Privacy-Preserving Data Market for Authentic Data. DE 2022 - Proceedings of the 1st International Workshop on Data Economy, Part of CoNEXT 2022: The First ACM Data Economy Workshop. New York, NY : Association of Computing Machinery, 2022. S. 15-20 (DE 2022 - Proceedings of the 1st International Workshop on Data Economy, Part of CoNEXT 2022).

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abstract = "Data marketplaces are online platforms that provide a way for individuals to monetize their (personal) data. In traditional data marketplaces, the data is uploaded to the marketplace platform in plain-text. Since the broker has access to all data, such marketplaces are risk to the users' privacy. We present a privacy-preserving marketplace that allows data owners to keep control over their data. We use secure multi-party computation to enable data consumers to evaluate expressive functions on a set of data. In our marketplace, the broker has neither access to the data nor the results of a function evaluation. Furthermore, our design ensures data-origin authenticity and enables data owners to define data-usage policies that are enforced by the computation nodes. In addition to the architecture of this private marketplace, we discuss a reference implementation. We also provide an evaluation of our approach, demonstrating its practicability.",

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N2 - Data marketplaces are online platforms that provide a way for individuals to monetize their (personal) data. In traditional data marketplaces, the data is uploaded to the marketplace platform in plain-text. Since the broker has access to all data, such marketplaces are risk to the users' privacy. We present a privacy-preserving marketplace that allows data owners to keep control over their data. We use secure multi-party computation to enable data consumers to evaluate expressive functions on a set of data. In our marketplace, the broker has neither access to the data nor the results of a function evaluation. Furthermore, our design ensures data-origin authenticity and enables data owners to define data-usage policies that are enforced by the computation nodes. In addition to the architecture of this private marketplace, we discuss a reference implementation. We also provide an evaluation of our approach, demonstrating its practicability.

AB - Data marketplaces are online platforms that provide a way for individuals to monetize their (personal) data. In traditional data marketplaces, the data is uploaded to the marketplace platform in plain-text. Since the broker has access to all data, such marketplaces are risk to the users' privacy. We present a privacy-preserving marketplace that allows data owners to keep control over their data. We use secure multi-party computation to enable data consumers to evaluate expressive functions on a set of data. In our marketplace, the broker has neither access to the data nor the results of a function evaluation. Furthermore, our design ensures data-origin authenticity and enables data owners to define data-usage policies that are enforced by the computation nodes. In addition to the architecture of this private marketplace, we discuss a reference implementation. We also provide an evaluation of our approach, demonstrating its practicability.

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BT - DE 2022 - Proceedings of the 1st International Workshop on Data Economy, Part of CoNEXT 2022

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KRAKEN: A Privacy-Preserving Data Market for Authentic Data

Abstract

Publikationsreihe

Konferenz

ASJC Scopus subject areas

Zugriff auf Dokument

Andere Dateien und Links

Fingerprint

Projekte

A-SIT - Zentrum für sichere Informationstechnologie Austria

EU - KRAKEN - Vermittlungs- und Marktplattform für personenbezogene Daten

Aktivitäten

KRAKEN: A Privacy-Preserving Data Market for Authentic Data

Dieses zitieren