Recent advances in blockchain technologies have provided exciting opportunities for decentralized applications. Specifically, blockchain-based smart contracts enable credible transactions without authorized third parties. The attractive properties of smart contracts facilitate distributed data vending, allowing for proprietary data to be securely exchanged on a blockchain. Distributed data vending can transform domains such as healthcare by encouraging data distribution from owners and enabling large-scale data aggregation. However, one key challenge in distributed data vending is the trade-off dilemma between the effectiveness of data retrieval, and the leakage risk from indexing the data. In this paper, we propose a framework for distributed data vending through a combination of data embedding and similarity learning. We illustrate our framework through a practical scenario of distributing and aggregating electronic medical records on a blockchain. Extensive empirical results demonstrate the effectiveness of our framework.
@article{arxiv.1803.05871,
title = {Distributed Data Vending on Blockchain},
author = {Jiayu Zhou and Fengyi Tang and He Zhu and Ning Nan and Ziheng Zhou},
journal= {arXiv preprint arXiv:1803.05871},
year = {2018}
}