🤖 AI Summary
本文提出了一种架构，利用可信执行环境(TEEs)和链上数字权利令牌(DRTs)来解决数据隐私问题，使数据所有者能够控制第三方如何处理其私有数据。
📝 Abstract
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.