Blockchain-Assisted Privacy-Preserving Data Computing Architecture for Web3

【Author】 Guo, Shaoyong; Zhang, Fan; Guo, Song; Xu, Siya; Qi, Feng

【Source】IEEE COMMUNICATIONS MAGAZINE

【影响因子】9.030

【Abstract】Web3 has received a lot of attention since its emergence. It aims to provide users with more diverse and vivid web services as well as the complete control over their own data. To support the development of Web3, privacy-preserving decentralized data computing schemes need to be studied. In earlier works, blockchain was used for trusted data sharing. However, due to the lack of computing attribute, blockchain is not capable enough to ensure the trustworthiness of the distributed computing process. Besides, the distributed computing method requires a large amount of data transmission and the current privacy protection researches seldom consider the problem of user privacy. In this article, we design a blockchain-assisted privacy-preserving distributed data computing architecture to break-through the limitations of existing researches. The proposed architecture ensures the secure and trustworthy computing with state channel and computing sandbox. We also design a sandbox location obfuscation method based on onion routing technology, making it difficult for attackers to identify the sandbox location or infer user privacy. Our solution fully considers the characteristics of Web3 and can well support the diverse Web3 applications.

【Keywords】Data privacy; Privacy; Trusted computing; Machine learning algorithms; Web services; Computer architecture; Routing; Semantic Web; Blockchains

【发表时间】2023 AUG

【收录时间】2023-10-25

【文献类型】理论模型

【主题类别】

区块链技术-核心技术-分布式计算