EDPS discusses data protection benefits of secure multi-party computation

The European Data Protection Supervisor (EDPS) has published a blog article on secure multi-party computation (SMPC), one of the next generations of privacy-enhancing technologies (PETs) moving from an academic concept to a practical solution. SMPC is presented as a means of reconciling the conflicting goals of data sharing and confidentiality. If the technology is proven viable, it could drive innovation across sectors such as health, finance, and law enforcement.

SMPC allows multiple organisations to jointly compute results and extract valuable insights from their private data, such as training machine learning models, without ever exposing the underlying data to one another. Unlike traditional encryption, which only protects data during storage or transmission, SMPC maintains confidentiality throughout the computation process itself, embodying a "compute without exposure" paradigm. This paradigm transforms data sharing from "data surrender" into a privacy-by-design approach.

By distributing computation and storage across multiple parties, SMPC also inherently mitigates the impact of external attacks, as there is no single data repository to breach. When combined with other PETs like homomorphic encryption, SMPC becomes part of a broader engineering toolkit that builds resilience into digital ecosystems.

Training Announcement: The IAPP Certified Information Privacy Technologist (CIPT) is a privacy-focused professional IT certificate from the IAPP that addresses data protection requirements and controls within complex technological environments. It explores the data lifecycle, privacy risk models and frameworks, the principles of Privacy by Design, and the role of privacy-enhancing technologies within the organisation. Find out more.