Digital Business Ecosystems (DBEs) increasingly rely on the sharing of sensitive data between stakeholders to foster collaboration. However, to restrict access to this data, traditional security mechanisms are often not sufficient. This paper investigates one such case, part of the Horizon Europe MUSIC360 project, where policymakers want to know the economic value of music at the industry level. We propose a solution design approach that systematically links scenario-specific requirements to technical features of Privacy-Preserving Computation (PPC). A proof-of-concept experiment using the Prio+ protocol demonstrates the usability of our approach by showing that the selected implementation meets both the functional and security requirements.

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Privacy-Preserving Computing in the Music Industry

  • Yulu Wang,
  • Charlotte van de Velde,
  • Sabine Oechsner,
  • Jaap Gordijn

摘要

Digital Business Ecosystems (DBEs) increasingly rely on the sharing of sensitive data between stakeholders to foster collaboration. However, to restrict access to this data, traditional security mechanisms are often not sufficient. This paper investigates one such case, part of the Horizon Europe MUSIC360 project, where policymakers want to know the economic value of music at the industry level. We propose a solution design approach that systematically links scenario-specific requirements to technical features of Privacy-Preserving Computation (PPC). A proof-of-concept experiment using the Prio+ protocol demonstrates the usability of our approach by showing that the selected implementation meets both the functional and security requirements.