Information Security 11 min read

Exploration and Reflections on Interoperability of Privacy Computing

This article presents a comprehensive overview of privacy‑computing interoperability in the financial sector, covering background challenges, the Beijing FinTech Alliance’s collaborative project structure, an industry‑level framework with technical and requirement layers, sub‑topic research results, achieved milestones, and future outlook for standardisation and ecosystem building.

DataFunSummit
DataFunSummit
DataFunSummit
Exploration and Reflections on Interoperability of Privacy Computing

The sharing session focuses on the exploration and thinking of privacy‑computing interoperability, introducing five main aspects: background and challenges, alliance project organization, industry‑level framework, interim results, and future outlook.

Background and Challenges: Data elements are crucial in finance, but privacy data circulation raises security concerns. Recent laws such as China’s Data Security Law and Personal Information Protection Law, along with the PBOC’s fintech development plan, demand orderly data sharing while ensuring safety. Privacy computing, which makes data computable but invisible, is key to building a secure data‑element network, yet fragmented platforms create interoperability problems.

Alliance Project Organization: The Beijing FinTech Industry Alliance Data Committee ("Jinke Alliance") launched two privacy‑computing topics in 2022, led by China UnionPay, involving over 50 institutions. After two months of one‑on‑one meetings, the project defined three focus areas: framework, interoperability, and work mechanisms, aiming for the minimal necessary system‑level interoperability.

Industry‑Level Interoperability Framework: The framework addresses both demand and technical layers. Demands include cost reduction, security, and detectability for financial institutions, tech firms, and testing agencies. Technically, it defines minimal necessary APIs, decouples the framework base from algorithm containers, and separates security operators from application algorithms.

The design separates management and data planes, allowing heterogeneous platforms to interoperate after adapting to common interfaces. Seven sub‑topics were formed (management elements, scheduling & container loading, secure operator services, transmission protocols, heterogeneous algorithm protocols, TEE interoperability, and ecosystem research), each delivering key technical points.

Interim Achievements: The research report was pre‑released in December 2022 and officially published in May 2023, gaining wide industry recognition. The alliance’s public account has released interpretations of six key technical points across two sub‑topics.

Future Outlook: Continued refinement of interfaces aims to become a de‑facto standard, supporting the construction of a data‑element infrastructure that underpins secure data flow in the financial industry.

Overall, the initiative demonstrates how collaborative technical standards can break platform silos, promote secure data sharing, and lay the groundwork for a robust privacy‑computing ecosystem.

privacy computingData Sharinginteroperabilityindustry standardsSecure Computationfinancial data security
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