Journal ArticleOpen Access
A Privacy-Preserving Mobile and Fog Computing Framework to Trace and Prevent COVID-19 Community Transmission
Authors
Author Affiliations
Queensland University of Technology, Jahangirnagar University, University of Houston, The University of Melbourne
Published InIEEE Journal of Biomedical and Health Informatics
Year2020
Citations70
Abstract
To slow down the spread of COVID-19, governments worldwide are trying to identify infected people, and contain the virus by enforcing isolation, and quarantine. However, it is difficult to trace people who came into contact with an infected person, which causes widespread community transmission, and mass infection. To address this problem, we develop an e-government Privacy-Preserving Mobile, and Fog computing framework entitled PPMF that can trace infected, and suspected cases nationwide. We use personal mobile devices with contact tracing app, and two types of stationary fog nodes, named Automatic Risk Checkers (ARC), and Suspected User Data Uploader Node (SUDUN), to trace community transmission alongside maintaining user data privacy. Each user's mobile device receives a Unique Encrypted Reference Code (UERC) when…
View at Publisher
BORR does not host full-text PDFs. The button above takes you to the original publisher.
Fields & Keywords
Physical SciencesComputer ScienceInformation SystemsCOVID-19 Digital Contact TracingMobile Health and mHealth ApplicationsPrivacy, Security, and Data ProtectionComputer securityInternet privacyTelecommunicationsWorld Wide WebBioinformaticsPathologyProgramming languageLinguisticsStructural engineering