Demarcating the Privacy Issues of Aarogya Setu App in Covid-19 Pandemic in India: An Exploration into Contact Tracing Mobile Applications from Elaboration Likelihood Model

Paper


Acharya, Nirmal and Sharma, Abhishek. 2022. "Demarcating the Privacy Issues of Aarogya Setu App in Covid-19 Pandemic in India: An Exploration into Contact Tracing Mobile Applications from Elaboration Likelihood Model." 4th International Conference on HCI for Cybersecurity, Privacy, and Trust (HCI-CPT 2022). 26 Jun - 01 Jul 2022 Switzerland . Springer. https://doi.org/10.1007/978-3-031-05563-8_28
Paper/Presentation Title

Demarcating the Privacy Issues of Aarogya Setu App in Covid-19 Pandemic in India: An Exploration into Contact Tracing Mobile Applications from Elaboration Likelihood Model

Presentation TypePaper
AuthorsAcharya, Nirmal and Sharma, Abhishek
Journal or Proceedings TitleProceedings of the 4th International Conference on HCI for Cybersecurity, Privacy, and Trust (HCI-CPT 2022)
Journal Citation13333, pp. 457-468
Number of Pages12
Year2022
PublisherSpringer
Place of PublicationSwitzerland
ISBN9783031055621
9783031055638
Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-031-05563-8_28
Web Address (URL) of Paperhttps://link.springer.com/chapter/10.1007/978-3-031-05563-8_28
Web Address (URL) of Conference Proceedingshttps://link.springer.com/book/10.1007/978-3-031-05563-8
Conference/Event4th International Conference on HCI for Cybersecurity, Privacy, and Trust (HCI-CPT 2022)
Event Details
4th International Conference on HCI for Cybersecurity, Privacy, and Trust (HCI-CPT 2022)
Delivery
Online
Event Date
26 Jun 2022 to end of 01 Jul 2022
Abstract

Demand for contract tracing applications is significantly increasing as governments across the globe are relying on these mobile apps to help combat the spread of the COVID-19 virus. However, while this technology has a potential benefit, there is widespread concern that consumers’ fears around privacy and data protection prevent them from downloading such apps. By focusing on this emerging crisis, in this study, we investigate the potential obstacles imposed by privacy concerns (i.e., the perceived risk of accepting the app permission, the perceived risk of providing the information). This study also investigates the popularity of Aarogya Setu, the Indian government’s COVID-19 app. In doing so, we examine privacy concerns through the theoretical lens of the Elaboration Likelihood Model and explore the download intentions of new users. Using the above dimensions of privacy, we then propose a conceptual framework that depicts the influence of privacy concerns over the download intention of new users. Lastly, this paper provides suggestions to allow the Aarogya Setu to improve its perceived reliability among its users and increase downloads.

KeywordsPrivacy concerns; COVID-19; Aarogya Setu; Elaboration likelihoodmodel; Download intention; Mobile applications
ANZSRC Field of Research 20204604. Cybersecurity and privacy
Public Notes

Files associated with this item cannot be displayed due to copyright restrictions.

SeriesLecture Notes in Computer Science
Byline AffiliationsUniversity of Southern Queensland
Swinburne University of Technology
Permalink -

https://research.usq.edu.au/item/z58y4/demarcating-the-privacy-issues-of-aarogya-setu-app-in-covid-19-pandemic-in-india-an-exploration-into-contact-tracing-mobile-applications-from-elaboration-likelihood-model

  • 29
    total views
  • 1
    total downloads
  • 0
    views this month
  • 0
    downloads this month

Export as

Related outputs

Predicting Co-Occurring Mental Health and Substance Use Disorders in Women: An Automated Machine Learning Approach
Acharya, Nirmal, Kar, Padmaja, Ally, Mustafa and Soar, Jeffrey. 2024. "Predicting Co-Occurring Mental Health and Substance Use Disorders in Women: An Automated Machine Learning Approach." Applied Sciences. 14 (4). https://doi.org/10.3390/app14041630