Homomorphic encryption for privacy-preserving data aggregation in data spaces

Privacy preservation in data spaces is a critical requirement for enabling trusted, cross-organizational data sharing aligned with European data governance principles. To address this gap, we present a technically enforced privacy-enhancing solution based on homomorphic encryption (HE) to enable privacy-preserving data aggregation. We built upon a Consumer-Aggregator-Provider (CAP) data computation architecture and implement a dedicated privacy module leveraging Eclipse Dataspace Components (EDC) and the Microsoft SEAL library to add HE capabilities to data spaces. Our solution is compliant with the Data Space Protocol (DSP) and is integrated within data spaces adhering to the International Data Spaces Association (IDSA) reference architecture. To demonstrate its practical applicability, we present a use case for energy consumption data aggregation by geographical zones and an analysis of the solution's performance and scalability. Our results demonstrate the feasibility and effectiveness of HE for privacy-preserving data aggregation in data spaces while identifying current limitations.