Details

Autor(en) / Beteiligte

• Ahmed, Nadeem
• Michelin, Regio A
• Xue, Wanli
• Ruj, Sushmita
• Malaney, Robert
• Kanhere, Salil S
• Seneviratne, Aruna
• Hu, Wen
• Janicke, Helge
• Jha, Sanjay K

Titel

A Survey of COVID-19 Contact Tracing Apps

Ist Teil von

• IEEE access, 2020, Vol.8, p.134577-134601

Ort / Verlag

Piscataway: IEEE

Erscheinungsjahr

2020

Link zum Volltext

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• The recent outbreak of COVID-19 has taken the world by surprise, forcing lockdowns and straining public health care systems. COVID-19 is known to be a highly infectious virus, and infected individuals do not initially exhibit symptoms, while some remain asymptomatic. Thus, a non-negligible fraction of the population can, at any given time, be a hidden source of transmissions. In response, many governments have shown great interest in smartphone contact tracing apps that help automate the difficult task of tracing all recent contacts of newly identified infected individuals. However, tracing apps have generated much discussion around their key attributes, including system architecture, data management, privacy, security, proximity estimation, and attack vulnerability. In this article, we provide the first comprehensive review of these much-discussed tracing app attributes. We also present an overview of many proposed tracing app examples, some of which have been deployed countrywide, and discuss the concerns users have reported regarding their usage. We close by outlining potential research directions for next-generation app design, which would facilitate improved tracing and security performance, as well as wide adoption by the population at large.