The Study of Privacy Protection of Scientific Data Sharing Based on Data Life Cycle
Dacheng Song, Chen Ming, Sheng Fan · Journal of Physics Conference Series · 2021
Abstract Scientific data sharing has become an important activity to promote modern research findings in which helps to reduce costs and save time for data collection, but it also brings certain privacy issues when using scientific data. First, based the network and literature survey method to described the basic conceptual of scientific data sharing, and discussed the issues of privacy violation in scientific data sharing during the data lifecycle. Second, tried to propose a privacy protection model and framework to prevent privacy violation. Finally, provided some suggestions for the current privacy protection in scientific data sharing from different perspectives. The study contributes to the scientific data sharing by shedding light on how to protect privacy of scientific data sharing through the privacy protection model and framework.