A privacy weaving pipeline for open big data
Yuan-Chih Yu, Dwen-Ren Tsai · 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) · 2016
The power of big data gives us an unprecedented chance to understand, analyze, and recreate the world, while open data ensures that power be shared and widely exploited. Open and big data has become the emerging topics for researchers and governments. Thus, the related privacy issues also become an emerging urgent problem. In this work, we propose a conceptual framework of privacy weaving pipeline dedicated for producing open and big data while preserving privacy. Within the processing pipeline, each step of the process flow considers the privacy assurance to manipulate datasets. However, the complexity of process flow is the same as normal data pipeline. The experimental prototype confirms the feasibility of framework design. We hope this work will facilitate the development of open and big data industry.