Privacy Guidelines for Contact Tracing Applications
arXiv:2004.13328
Abstract
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.
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References in corpus (4)
- Contact Tracing Mobile Apps for COVID-19: Privacy Considerations and Related Trade-offs
- Mobile phone data and COVID-19: Missing an opportunity?
- Apps Gone Rogue: Maintaining Personal Privacy in an Epidemic
- Assessing Disease Exposure Risk with Location Data: A Proposal for Cryptographic Preservation of Privacy
Cited by in corpus (6)
- COVID-19 and Your Smartphone: BLE-based Smart Contact Tracing
- Short Paper: Privacy Comparison of Contact Tracing Mobile Applications for COVID-19
- Epidemic Exposure Notification with Smartwatch: A Proximity-Based Privacy-Preserving Approach
- SARiSsa -- A Mobile Application for the Proactive Control of SARS-CoV-2 Spread
- Infection Risk Score: Identifying the risk of infection propagation based on human contact
- A Note on Cryptographic Algorithms for Private Data Analysis in Contact Tracing Applications