论文标题
流行数据收集中的隐私保护
Privacy Preservation in Epidemic Data Collection
论文作者
论文摘要
这项工作的灵感来自于19 Covid-19的爆发，以及我们在收集有关该疾病的数据时发现的一些挑战。为此，我们旨在帮助收集有关公民和疾病的数据，而无需冒险的个人隐私。具体而言，我们专注于如何确定全国人口的密度，如何追踪公民之间的接触，如何确定感染的位置以及如何确定疾病传播的时间表。我们提出的方法是保护隐私，并且依靠应用程序自愿安装在公民的智能手机上。因此，任何人都可以选择不参加。但是，这些方法的准确性取决于大部分人口的参与。
This work is inspired by the outbreak of COVID-19, and some of the challenges we have observed with gathering data about the disease. To this end, we aim to help collect data about citizens and the disease without risking the privacy of individuals. Specifically, we focus on how to determine the density of the population across the country, how to trace contact between citizens, how to determine the location of infections, and how to determine the timeline of the spread of the disease. Our proposed methods are privacy-preserving and rely on an app to be voluntarily installed on citizens' smartphones. Thus, any individual can choose not to participate. However, the accurateness of the methods relies on the participation of a large percentage of the population.
