A Greener Approach to Privacy-Aware Cross-Border Data Federation through Knowledge Reuse
Papatsaroucha, Dimitra, Pityanou, Konstantina, Sayeed, Sarwar, Papadopoulos, Pavlos, Kasimatis, Dimitrios, Zotou, Maria, Kourtis, Michail-Alexandros, Markakis, Evangelos · Edinburgh Napier Research Repository (Edinburgh Napier University) · 2025
As the need for privacy-preserving, cross-border data federation grows, emerging platforms struggle to find a balance between privacy-aware data sharing and computations and practical scalability and sustainability issues. Homomorphic Encryption (HE) allows for operations to be performed entirely in the encrypted domain without exposing or leaking sensitive data; however, this does not come without energy and latency costs, due to HE’s computational expense. In this research, a Knowledge Store and Reuse Framework is designed and proposed as a greener approach to privacy-aware cross-border data federation, prioritizing sustainability and enabling the selective reuse of privacy-preserving search and computation results. When incorporated into a wider federated analytics platform based on data sovereignty, accountability, and GDPR compliance, the proposed framework provides a more environmentally friendly means of dealing with privacy-sensitive data flows. The solution allows future Data Consumers to avoid duplicate encrypted actions by storing search and computations results of already performed processes in an IPFS-based Knowledge Repository and enabling semantic similarity analysis via a Knowledge Graph and Automated Analysis Tool. To demonstrate how the presented solution reduces the energy footprint of encrypted data operations while maintaining full compliance and traceability, this study provides the system architecture, consent-aware workflow, and realistic knowledge reuse scenarios, introducing a new step toward successful and scalable privacy-aware data federation across domains.