This paper explores the integration of advanced cryptographic techniques for secure computation in data spaces to enable secure and trusted data sharing, which is essential for the evolving data economy. In addition, the paper examines the role of data intermediaries, as outlined in the EU Data Governance Act, in data spaces and specifically introduces the idea of trustless intermediaries that do not have access to their users' data. Therefore, we exploit the introduced secure computation methods, i.e. Secure Multi-Party Computation (MPC) and Fully Homomorphic Encryption (FHE), and discuss the security benefits. Overall, we identify and address key challenges for integration, focusing on areas such as identity management, policy enforcement, node selection, and access control, and present solutions through real-world use cases, including air traffic management, manufacturing, and secondary data use. Furthermore, through the analysis of practical applications, this work proposes a comprehensive framework for the implementation and standardization of secure computing technologies in dynamic, trustless data environments, paving the way for future research and development of a secure and interoperable data ecosystem.

翻译：本文探讨了在数据空间中集成先进密码学技术以实现安全计算，从而促进安全可信的数据共享，这对于不断发展的数据经济至关重要。此外，本文依据《欧盟数据治理法案》的框架，审视了数据中介在数据空间中的作用，并特别引入了无信任中介的概念，这类中介无法访问其用户的数据。为此，我们利用了所引入的安全计算方法，即安全多方计算（MPC）和全同态加密（FHE），并讨论了其安全优势。总体而言，我们识别并解决了集成的关键挑战，重点关注身份管理、策略执行、节点选择和访问控制等领域，并通过实际用例（包括空中交通管理、制造业和二次数据利用）提出了解决方案。此外，通过对实际应用的分析，本研究提出了一个在动态、无信任数据环境中实施和标准化安全计算技术的综合框架，为未来构建安全且可互操作的数据生态系统的研究与开发铺平了道路。