CRJul 14, 2020

BDTF: A Blockchain-Based Data Trading Framework with Trusted Execution Environment

arXiv:2007.06813v115 citations
Originality Incremental advance
AI Analysis

This addresses the issue of trust and fairness for data buyers and sellers in decentralized data trading, though it is incremental as it combines existing technologies like blockchain and TEE.

The authors tackled the problem of dishonest centralized platforms in data markets by proposing a blockchain-based data trading framework with Trusted Execution Environment (TEE), which effectively ensures fair data transactions as demonstrated through implementation on Ethereum and Intel SGX.

The need for data trading promotes the emergence of data market. However, in conventional data markets, both data buyers and data sellers have to use a centralized trading platform which might be dishonest. A dishonest centralized trading platform may steal and resell the data seller's data, or may refuse to send data after receiving payment from the data buyer. It seriously affects the fair data transaction and harm the interests of both parties to the transaction. To address this issue, we propose a novel blockchain-based data trading framework with Trusted Execution Environment (TEE) to provide a trusted decentralized platform for fair data trading. In our design, a blockchain network is proposed to realize the payments from data buyers to data sellers, and a trusted exchange is built by using a TEE for the first time to achieve fair data transmission. With these help, data buyers and data sellers can conduct transactions directly. We implement our proposed framework on Ethereum and Intel SGX, security analysis and experimental results have demonstrated that the framework proposed can effectively guarantee the fair completion of data tradings.

Foundations

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