Blockchain-based privacy-preserving framework for multi-party data sharing in emerging IoT - Pingchuan Xu; Junxi Liang; Yuxuan Luo; Xingyi Peng; Zhe Sun (Blockchain)
With the arrival of the Internet of Things era, the information world can perceive every corner of the real world, providing a steady stream of data collection for its data analysis. However, multi-party data sharing and security analysis have become a challenge that must be solved as Internet of Things technology evolves to the next level. Currently, most data sharing must introduce a trusted entity to perform cross-domain data fusion and protect privacy from a global perspective. Unless trusted entities can ensure that the privacy preserving mechanism is implemented properly, once the data is leaked, it will cause great harm to the public and to private interests. In this paper, we propose a new privacy preserving framework to tackle the problem of trusted entities in multi-party data sharing, which is based on a distributed consensus mechanism on blockchain. We analyze and abstract the privacy and availability requirements of all participants in multi-party data sharing and design a collaborative on-chain-off-chain privacy protection mechanism. To ensure that no one participant's private data is not accessed by each other, promote fair transaction of smart contracts, and achieve a balance among privacy preserving effects, transaction fairness, service quality, and execution efficiency from a global perspective.