Dissecting contact tracing apps in the Android platform

Contact tracing has historically been used to retard the spread of infectious diseases, but if it is exercised by hand in large-scale, it is known to be a resource-intensive and quite deficient process. Nowadays, digital contact tracing has promptly emerged as an indispensable asset in the global fi...

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Bibliographic Details
Published in:PloS one 2021-05, Vol.16 (5), p.e0251867-e0251867
Main Authors: Kouliaridis, Vasileios, Kambourakis, Georgios, Chatzoglou, Efstratios, Geneiatakis, Dimitrios, Wang, Hua
Format: Article
Language:English
Subjects:
Applications programs
Biology and life sciences
Bluetooth
Communications systems
Computer and Information Sciences
Contact tracing
Control
Coronaviruses
COVID-19
Engineering and Technology
Epidemics
Europa
Europe
Evaluation
Exposure
Infectious diseases
Informatics
Information systems
Medicine and Health Sciences
Methodology
Methods
Methyltestosterone
Mobile applications
Mobile operating systems
Pandemics
Population
Privacy
Public health
Research facilities
Social Sciences
Software
Systems engineering
Technology application
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Summary:Contact tracing has historically been used to retard the spread of infectious diseases, but if it is exercised by hand in large-scale, it is known to be a resource-intensive and quite deficient process. Nowadays, digital contact tracing has promptly emerged as an indispensable asset in the global fight against the coronavirus pandemic. The work at hand offers a meticulous study of all the official Android contact tracing apps deployed hitherto by European countries. Each app is closely scrutinized both statically and dynamically by means of dynamic instrumentation. Depending on the level of examination, static analysis results are grouped in two axes. The first encompasses permissions, API calls, and possible connections to external URLs, while the second concentrates on potential security weaknesses and vulnerabilities, including the use of trackers, in-depth manifest analysis, shared software analysis, and taint analysis. Dynamic analysis on the other hand collects data pertaining to Java classes and network traffic. The results demonstrate that while overall these apps are well-engineered, they are not free of weaknesses, vulnerabilities, and misconfigurations that may ultimately put the user security and privacy at risk.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0251867