Enhancing the data privacy for public data lakes
Yihua Chen, Hsin-Hsin Chen, Po-Chun Jimmy Huang · 2018 IEEE International Conference on Applied System Invention (ICASI) · 2018
With the rapid development of big data technologies, the value of data are discovered in a wide spectrum of application scenarios. How to effectively share valuable data therefore becomes a design focus of data lakes, which is a popular means of data sharing. Unfortunately, the privacy issues due to data sharing remains a missing piece in the data lake designs, which become a barrier of data sharing between foreign peers that might not completely trust each other. In this paper, we propose a novel framework for public data lakes to control and protect the data privacy of data sharing. The major objective of this work is to boost the circulation of valuable data for big data analytics, and promote the development of big data technologies.