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

可信研究环境（TRE）被许多组织用来安全地管理研究中的敏感数据。尽管存在共同的需求，但目前运营商之间的基础设施或部署几乎没有标准化，导致工作重复并阻碍服务改进。TREEHOOSE旨在建立我们将TRE托管NHS数据迁移到公共云的经验，以造福其他运营商。我们还将加入新的Enclave计算能力，以实现无互信计算，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，同时保持安全性和信任。Secure Enclaves超越了传统的TRE基础设施，增加了额外的屏障，以防止软件算法泄漏数据。将开发一个工具包，研究人员可以将他们的AI或其他分析代码添加到云TRE中执行，安全地知道他们的代码受到保护，即使是TRE运营商也不会进行反向工程或未经授权的共享，用密码学-TREEHOOSE将能够更广泛地采用TREs并提高工作模式的安全性，从而使大规模的研究数据分析成为可能，同时保持最大限度的数据保护。

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.