AI 中文总结
提出利用TEE和链上数字版权令牌实现数据池的可验证计算，通过受限计算权限保护隐私，并在Solana上验证了可行性。
AI 中文摘要
我们提出了一种架构，使数据所有者能够利用可信执行环境（TEEs）将私有数据组合成数据池，并通过向第三方数据分析师签发范围受限的计算权限（编码为数字版权令牌（DRTs））来管理这些数据池。每个DRT将特定的开源代码绑定到一个数据池，并在分布式账本上发行和赎回。数据分析师可以获得在TEE内对合并后的密封数据执行开源代码的权利，并接收该代码执行的结果，但无法获取底层数据。我们主张一种以控制为中心的隐私观，即数据创建者对其数据的处理方式保留事前控制权。一个参考实现可在密封数据集上运行WebAssembly（WASM）/Python作业，并在Solana上记录赎回操作，展示了该平台的可行性与局限性。
英文摘要
We present an architecture that enables data owners to combine private data into data pools using Trusted Execution Environments (TEEs) and manage these pools by issuing narrowly scoped computational rights, encoded as Digital Rights Tokens (DRTs), to third-party data analysts. Each DRT binds specific open-source code to a pool and is issued and redeemed on a distributed ledger. Data analysts can obtain the right to execute open-source code on the combined sealed data inside a TEE and receive the result from this code execution, but not the underlying data. We argue for a control-centric view of privacy in which creators retain ex ante control over how their data is processed. A reference implementation runs WebAssembly (WASM)/Python jobs over sealed datasets and records redemptions on Solana, illustrating the feasibility and limitations of the platform.
Comments15 pages, 1 figure, 2 appendices
