Privacy Guidelines for Contact Tracing Applications Article Swipe
Manish Shukla
,
Rajan M. A
,
Sachin Lodha
,
Gautam Shroff
,
Ramesh Raskar
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2004.13328
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2004.13328
Contact tracing is a very powerful method to implement and enforce social distancing to avoid spreading of infectious diseases. The traditional approach of contact tracing is time consuming, manpower intensive, dangerous and prone to error due to fatigue or lack of skill. Due to this there is an emergence of mobile based applications for contact tracing. These applications primarily utilize a combination of GPS based absolute location and Bluetooth based relative location remitted from user's smartphone to infer various insights. These applications have eased the task of contact tracing; however, they also have severe implication on user's privacy, for example, mass surveillance, personal information leakage and additionally revealing the behavioral patterns of the user. This impact on user's privacy leads to trust deficit in these applications, and hence defeats their purpose. In this work we discuss the various scenarios which a contact tracing application should be able to handle. We highlight the privacy handling of some of the prominent contact tracing applications. Additionally, we describe the various threat actors who can disrupt its working, or misuse end user's data, or hamper its mass adoption. Finally, we present privacy guidelines for contact tracing applications from different stakeholder's perspective. To best of our knowledge, this is the first generic work which provides privacy guidelines for contact tracing applications.
Related Topics
Concepts
Contact tracing
Tracing
Internet privacy
Computer science
Computer security
Operating system
Coronavirus disease 2019 (COVID-19)
Medicine
Pathology
Infectious disease (medical specialty)
Disease
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2004.13328
- https://arxiv.org/pdf/2004.13328
- OA Status
- green
- Cited By
- 21
- References
- 15
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3021495674
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W3021495674Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2004.13328Digital Object Identifier
- Title
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Privacy Guidelines for Contact Tracing ApplicationsWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
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2020-04-28Full publication date if available
- Authors
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Manish Shukla, Rajan M. A, Sachin Lodha, Gautam Shroff, Ramesh RaskarList of authors in order
- Landing page
-
https://arxiv.org/abs/2004.13328Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2004.13328Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2004.13328Direct OA link when available
- Concepts
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Contact tracing, Tracing, Internet privacy, Computer science, Computer security, Operating system, Coronavirus disease 2019 (COVID-19), Medicine, Pathology, Infectious disease (medical specialty), DiseaseTop concepts (fields/topics) attached by OpenAlex
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21Total citation count in OpenAlex
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2024: 1, 2023: 2, 2022: 2, 2021: 9, 2020: 7Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.insights. | 79 |
| abstract_inverted_index.primarily | 58 |
| abstract_inverted_index.prominent | 158 |
| abstract_inverted_index.revealing | 107 |
| abstract_inverted_index.scenarios | 138 |
| abstract_inverted_index.spreading | 15 |
| abstract_inverted_index.behavioral | 109 |
| abstract_inverted_index.consuming, | 27 |
| abstract_inverted_index.distancing | 12 |
| abstract_inverted_index.guidelines | 188, 211 |
| abstract_inverted_index.infectious | 17 |
| abstract_inverted_index.intensive, | 29 |
| abstract_inverted_index.knowledge, | 201 |
| abstract_inverted_index.smartphone | 75 |
| abstract_inverted_index.application | 143 |
| abstract_inverted_index.combination | 61 |
| abstract_inverted_index.implication | 94 |
| abstract_inverted_index.information | 103 |
| abstract_inverted_index.traditional | 20 |
| abstract_inverted_index.additionally | 106 |
| abstract_inverted_index.applications | 52, 57, 81, 192 |
| abstract_inverted_index.perspective. | 196 |
| abstract_inverted_index.Additionally, | 162 |
| abstract_inverted_index.applications, | 125 |
| abstract_inverted_index.applications. | 161, 215 |
| abstract_inverted_index.stakeholder's | 195 |
| abstract_inverted_index.surveillance, | 101 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/16 |
| sustainable_development_goals[0].score | 0.550000011920929 |
| sustainable_development_goals[0].display_name | Peace, Justice and strong institutions |
| citation_normalized_percentile |