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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8121305/ https://www.ncbi.nlm.nih.gov/pubmed/33989350 http://dx.doi.org/10.1371/journal.pone.0251867 |
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author | Kouliaridis, Vasileios Kambourakis, Georgios Chatzoglou, Efstratios Geneiatakis, Dimitrios Wang, Hua |
author_facet | Kouliaridis, Vasileios Kambourakis, Georgios Chatzoglou, Efstratios Geneiatakis, Dimitrios Wang, Hua |
author_sort | Kouliaridis, Vasileios |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8121305 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-81213052021-05-24 Dissecting contact tracing apps in the Android platform Kouliaridis, Vasileios Kambourakis, Georgios Chatzoglou, Efstratios Geneiatakis, Dimitrios Wang, Hua PLoS One Research Article 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. Public Library of Science 2021-05-14 /pmc/articles/PMC8121305/ /pubmed/33989350 http://dx.doi.org/10.1371/journal.pone.0251867 Text en © 2021 Kouliaridis et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Kouliaridis, Vasileios Kambourakis, Georgios Chatzoglou, Efstratios Geneiatakis, Dimitrios Wang, Hua Dissecting contact tracing apps in the Android platform |
title | Dissecting contact tracing apps in the Android platform |
title_full | Dissecting contact tracing apps in the Android platform |
title_fullStr | Dissecting contact tracing apps in the Android platform |
title_full_unstemmed | Dissecting contact tracing apps in the Android platform |
title_short | Dissecting contact tracing apps in the Android platform |
title_sort | dissecting contact tracing apps in the android platform |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8121305/ https://www.ncbi.nlm.nih.gov/pubmed/33989350 http://dx.doi.org/10.1371/journal.pone.0251867 |
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