Trusted Research Environment and Enclave for Hosting Open Original Science Exploration (TREEHOOSE)

许多组织使用可信研究环境（TREs）来安全地管理研究中的敏感数据。尽管需求具有共性，但目前运营商之间的基础设施或部署几乎没有标准化，导致重复工作，阻碍了服务的改进。TREEHOOSE的目标是建立在我们将托管NHS数据的TRE迁移到公共云的经验之上，以使其他运营商受益。我们还将包括Enclave计算的新功能，以实现相互信任的计算，保护用户的IP和代码以及数据。我们将发布开源工具，以简化在公共云基础设施上构建和运营TREs的过程，同时保持安全性和信任。安全飞地通过增加额外的屏障来防止软件算法泄露数据，从而超越了传统的TRE基础设施。将开发一个工具包，研究人员可以在其中添加他们的人工智能或其他分析代码，以便在云TRE中执行，因为他们的代码受到保护，不受逆向工程或未经授权的共享，即使是TRE运营商，也具有加密验证的可重复依赖关系。TREEHOOSE将更广泛地采用TREs，并增加安全工作模式，从而使大规模研究数据分析成为可能，同时保持最大的数据保护。

Trusted Research Environments (TREs) are used by many organisations to securely manage sensitive data for research. Despite the commonality of need there is currently little standardisation of infrastructure or deployment between operators, leading to duplication of effort and impeding service improvement. TREEHOOSE aims to build on our experience of migrating a TRE hosting NHS data to public cloud for the benefit of other operators. We will also to include a new capability of Enclave computing to achieve mutually trust-free computation, protecting users’ IP and code as well as the data.We will release open-source tooling to streamline building and operating TREs on public cloud infrastructure whilst maintaining security and trust. Secure Enclaves go beyond the traditional TRE infrastructure by adding additional barriers to prevent software algorithms from leaking data. A kit will be developed into which researchers can add their AI or other analytical code for execution within a cloud TRE, safe in the knowledge that their code is protected from reverse-engineering or unauthorised sharing even by the TRE operators, with cryptographically-verified repeatable dependencies.TREEHOOSE will enable wider adoption of TREs and increased security modes of working thereby making possible research data analysis at scale while maintaining maximum data protections.