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Approach for GDPR Compliant Detection of COVID-19 Infection Chains

  • 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 setWhile 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.show moreshow less

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Metadaten
Document Type:Report
Zitierlink: https://opus.hs-offenburg.de/4287
Bibliografische Angaben
Title (English):Approach for GDPR Compliant Detection of COVID-19 Infection Chains
Author:Dirk WesthoffStaff MemberGND, Louis TajanStaff Member
Year of Publication:2020
Page Number:7
Language:English
Inhaltliche Informationen
Institutes:Fakultät Medien und Informationswesen (M+I) (bis 21.04.2021)
Institutes:Bibliografie
Tag:COVID-19; Corona
Formale Angaben
Open Access: Open Access 
Licence (German):License LogoUrheberrechtlich geschützt
ArXiv Id:http://arxiv.org/abs/2007.08248