| Authors: | Ghilezan, Silvia Stefanović, Tamara |
Affiliations: | Mathematics Mathematical Institute of the Serbian Academy of Sciences and Arts |
Title: | Privacy-preserving contact tracing | Series/Report no.: | De Gruyter Proceedings | First page: | 171 | Last page: | 182 | Related Publication(s): | Mathematics for Human Flourishing in the Time of COVID-19 and Post COVID-19 : Proceedings of the Workshop held at the Faculty of Mechanical Engineering, University of Niš, Niš, 21 of October 2020 | Issue Date: | 2023 | ISBN: | 978-3-11-073862-9 | DOI: | 10.1515/9783110734119-015 | Abstract: | Digital contact tracing apps represent a significant contribution of computer science to the global fight with COVID-19 pandemic. Digital contact tracing apps are designed towarn people if they have been in contact with an infected person. They have proven useful to slow down transmission for many infectious diseases, nonetheless they also rose many privacy concerns. In this paper, we explore the main privacy concerns in digital contact tracing. |
Publisher: | De Gruyter |
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