Business model implications of privacy-preserving technologies in data marketplaces: The case of multi-party computation

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Abstract

Privacy-preserving technologies could allow data marketplaces to deliver technical assurances to companies on data privacy and control. However, how such technologies change the business model of data marketplaces is not fully understood. This paper aims to bridge this gap by focusing on multi-party computation (MPC) as a cryptographic technology that is currently being hyped. Based on interviews with privacy and security experts, we find that MPC enables data marketplaces to employ a “privacy-as-a-service” business model, which goes beyond privacy-preserving data exchange. Depending on the architecture, MPC could transform data marketplaces into data brokers or data aggregators. More complex architectures might lead to more robust security guarantees and lower trust requirements towards data marketplace operators. Furthermore, MPC enables new offerings of privacy-preserving analytics and services as new revenue sources. Our findings contribute to developing business models of privacy-preserving data marketplaces to unlock the potential of data sharing in a digitized economy.
Original languageEnglish
Title of host publication29th European Conference on Information Systems (ECIS 2021)
Subtitle of host publication Human Values Crisis in a Digitizing World
PublisherAssociation of the Information Systems (AIS)
Pages1-16
Publication statusPublished - 2021
Event29th European Conference on Information Systems (ECIS 2021) A Virtual AIS Conference: Human Values Crisis in a Digitizing World - , Morocco
Duration: 14 Jun 202116 Jun 2021

Conference

Conference29th European Conference on Information Systems (ECIS 2021) A Virtual AIS Conference
CountryMorocco
Period14/06/2116/06/21

Keywords

  • data marketplaces
  • multi-party computation
  • privacy-as-a-service
  • business model

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