Privacy-Preserving Contact Tracing for Curbing the Spread of Infectious Disease

被引:1
|
作者
Li, Hui [1 ]
机构
[1] Beijing Univ Chem Technol, Beijing, Peoples R China
基金
国家重点研发计划;
关键词
Contact Tracing; Private Set Intersection; Privacy-Preserving Data Processing; Privacy Problem; Engineering Ethics;
D O I
10.4018/JDM.324075
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The world is facing one of the greatest public health threats in modern history. Various techniques based on contact tracing have been developed to support non-pharmaceutical interventions. The growing evidence shows that app-based contact tracing can reduce the spread of COVID-19 if a certain proportion of the population uses the apps. However, the risk of privacy breaches that comes with such apps has long been a public concern which may hinder the uptake of the apps. In this paper, the authors attempt to find a solution to complete the spatiotemporal intersection computation without exposing the infected patient location and the user location to one another. The authors implement the solution in the WeChat applet to aid the local health center. This study conducts experiments for six scenarios to justify the applicability of the applet. Experiment results indicate that the applet is a promising non-pharmaceutical tool for curbing the spread of COVID-19.
引用
收藏
页数:17
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