论文标题
符合GDPR的COVID-19感染链的检测方法
Approach for GDPR Compliant Detection of COVID-19 Infection Chains
论文作者
论文摘要
尽管在欧洲国家 /地区广泛讨论了跟踪移动设备用户的前景，以抵消Covid-19的传播，但我们提出了一个基于Bloom过滤器的建筑，以提供用户的位置隐私并防止大规模监视。我们采用基于BLOOM过滤器数据结构的解决方案，该解决方案允许第三方政府机构在移动电信公司的访问日志文件上执行一些隐私的设置关系。通过计算集合关系，鉴于两个已确定的人的知识，政府机构具有一种工具，可以提供（可能的）感染链，从初始感染到最终受感染的用户，无论其在全球范围内哪个位置。我们方法的好处是，可以确定中间可能的感染用户并随后由该机构联系。通过这种方法，我们声明将揭示可能的受感染用户的身份，并保留其他人的位置隐私。在此范围内，它符合该领域的一般数据保护法规（GDPR）要求。
While prospect of tracking mobile devices' users is widely discussed all over European countries to counteract COVID-19 propagation, we propose a Bloom filter based construction providing users' location privacy and preventing mass surveillance. We apply a solution based on Bloom filters data structure that allows a third party, a government agency, to perform some privacy-preserving set relations on a mobile telco's access logfile. By computing set relations, the government agency, given the knowledge of two identified persons, has an instrument that provides a (possible) infection chain from the initial to the final infected user no matter at which location on a worldwide scale they are. The benefit of our approach is that intermediate possible infected users can be identified and subsequently contacted by the agency. With such approach, we state that solely identities of possible infected users will be revealed and location privacy of others will be preserved. To this extent, it meets General Data Protection Regulation (GDPR)requirements in this area.
