Trusted execution environments enable secure data sharing with digital rights tokens
Verifiable Computation with Trusted Execution Environments and On-Chain Digital Rights Tokens
Cryptography and SecurityDistributed, Parallel, and Cluster Computing
Summary
Sometimes people want to share data for analysis but keep it private. This paper shows a way to combine private data securely so that only approved code can run on it, without revealing the data itself. The authors use special secure zones called Trusted Execution Environments to protect the data and issue digital tokens that give others permission to run specific code on the data. The process is tracked on a blockchain to ensure transparency. They built a working example using WebAssembly and the Solana blockchain to show this can actually work.
What this means in practice
- •For enterprise data teams: Manage access to combined sensitive datasets by issuing precise computational permissions tracked on a blockchain.
- •For blockchain developers: Implement on-chain tokens that control and audit rights to execute code on protected data within trusted execution environments.
Authors
Bingle Stegmann Kruger, Co-Pierre Georg
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.