TY - GEN
T1 - A Study of Users' Privacy Preferences for Data Sharing on Symptoms-Tracking/Health App
AU - Asif, Hafiz
AU - Vaidya, Jaideep
N1 - Funding Information:
We thank Dr. Periklis A. Papakonstantinou (MSIS Department), Dr. Stephanie Shiau (Department of Biostatistics and Epidemiology), and Dr. Vivek Singh (Department of Library and Information Science) from Rutgers University for their help in designing the questionnaire. Research reported in this publication was supported by the National Institutes of Health (award# R35GM134927) and the National Science Foundation (award# CNS-2027789). The content is solely the responsibility of the authors and does not necessarily represent the official views of the agencies funding the research.
Publisher Copyright:
© 2022 ACM.
PY - 2022/11/7
Y1 - 2022/11/7
N2 - Symptoms-tracking applications allow crowdsensing of health and location related data from individuals to track the spread and outbreaks of infectious diseases. During the COVID-19 pandemic, for the first time in history, these apps were widely adopted across the world to combat the pandemic. However, due to the sensitive nature of the data collected by these apps, serious privacy concerns were raised and apps were critiqued for their insufficient privacy safeguards. The Covid Nearby project was launched to develop a privacy-focused symptoms-tracking app and to understand the privacy preferences of users in health emergencies. In this work, we draw on the insights from the Covid Nearby users' data, and present an analysis of the significantly varying trends in users' privacy preferences with respect to demographics, attitude towards information sharing, and health concerns, e.g. after being possibly exposed to COVID-19.
AB - Symptoms-tracking applications allow crowdsensing of health and location related data from individuals to track the spread and outbreaks of infectious diseases. During the COVID-19 pandemic, for the first time in history, these apps were widely adopted across the world to combat the pandemic. However, due to the sensitive nature of the data collected by these apps, serious privacy concerns were raised and apps were critiqued for their insufficient privacy safeguards. The Covid Nearby project was launched to develop a privacy-focused symptoms-tracking app and to understand the privacy preferences of users in health emergencies. In this work, we draw on the insights from the Covid Nearby users' data, and present an analysis of the significantly varying trends in users' privacy preferences with respect to demographics, attitude towards information sharing, and health concerns, e.g. after being possibly exposed to COVID-19.
KW - covid-19
KW - privacy preferences
KW - symptoms-tracking
KW - user stud
UR - http://www.scopus.com/inward/record.url?scp=85143252341&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85143252341&partnerID=8YFLogxK
U2 - 10.1145/3559613.3563202
DO - 10.1145/3559613.3563202
M3 - Conference contribution
AN - SCOPUS:85143252341
T3 - WPES 2022 - Proceedings of the 21st Workshop on Privacy in the Electronic Society, co-located with CCS 2022
SP - 109
EP - 113
BT - WPES 2022 - Proceedings of the 21st Workshop on Privacy in the Electronic Society, co-located with CCS 2022
PB - Association for Computing Machinery, Inc
T2 - 21st Workshop on Privacy in the Electronic Society, WPES 2022
Y2 - 7 November 2022
ER -