Verifiable Computation with Trusted Execution Environments and On-Chain Digital Rights Tokens
Researchers propose TEE-sealed data pools with on-chain Digital Rights Tokens so analysts run code without seeing underlying data.
The paper proposes combining private datasets into sealed pools inside Trusted Execution Environments and governing access with Digital Rights Tokens recorded on a ledger. Each token binds specific open-source code to a pool so an analyst can execute that code inside the TEE and receive only the result, not the raw data. A reference implementation runs WebAssembly and Python jobs over sealed datasets and records redemptions on Solana. The authors frame privacy as ex ante control by data creators and discuss feasibility and limits.
- Data owners pool sealed data in TEEs and issue narrowly scoped computational rights.
- Digital Rights Tokens bind open-source code to a pool and redeem on-chain.
- Analysts receive computation results but not the underlying private data.
- Reference jobs use WebAssembly and Python, with redemptions recorded on Solana.
- Products
- SolanaWebAssembly
From the original article
1 min read at arxiv.orgWe 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.
By Bingle Stegmann Kruger · arxiv.org
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