CPchain: A Copyright-Preserving Crowdsourcing Data Trading Framework Based on Blockchain

Dingjie Sheng, Mingjun Xiao, An Liu, Xiang Zou, Baoyi An, Sheng Zhang

Abstract: Crowdsourcing data trading is a novel paradigm in which the crowdsourcing technology is adopted to collect big data for trading. At present, existing crowdsourcing data trading systems usually depend on a trusted broker and haven't considered the truthfulness and the quality of data (QoD) simultaneously. Besides, copyright protection is the another issue that has not been properly addressed. To tackle these problems, we propose a Copyright-Preserving crowdsourcing data trading framework based on Blockchain, named CPchain, which mainly includes a smart contract. We design an auction algorithm based on semantic similarity to guarantee the truthfulness and individual rationality while ensuring QoD. Moreover, we combine digital fingerprint technology with blockchain to protect data copyright without a third-party certification authority. Furthermore, we develop a simple prototype of our proposed trading framework on the Ethereum test network. We have carried out a lot of experiments to demonstrate the significant performances of our framework.