BBAuthors: Kim, H.; Advisor: -; Participants: Kim, S.; Hwang, J. Y.; Seo, C. (2019)
A blockchain as a trustworthy and secure decentralized and distributed network has been emerged for many applications such as in banking, nance, insurance, healthcare and business. Recently, many communities in blockchain networks want to deploy machine learning models to get meaningful knowledge from geographically distributed large-scale data owned by each participant. To run a learning model without data centralization, distributed machine learning (DML) for blockchain networks has been studied. While several works have been proposed, privacy and security have not been suf ciently addressed, and as we show later, there are vulnerabilities in the architecture and limitations in terms of ef ciency. In this paper, we propose a privacy-preserving DML model for a permissioned blockch... 
