Privacy-preserving contact tracing and public risk assessment using blockchain for COVID-19 pandemic

Valente Klaine, P. , Zhang, L. , Zhou, B., Sun, Y. , Xu, H. and Imran, M. (2020) Privacy-preserving contact tracing and public risk assessment using blockchain for COVID-19 pandemic. IEEE Internet of Things Magazine, 3(3), pp. 58-63. (doi: 10.1109/IOTM.0001.2000078)

Abstract

Due to the number of confirmed cases and casualties of the new COVID-19 virus diminishing day after day, several countries around the world are discussing how to return to the new normal way of life. In order to keep the spread of the disease under control and avoid a second wave of infection, one alternative being considered is the utilization of contact tracing. However, despite several alternatives being available, contact tracing still faces issues in terms of maintaining user privacy and security, making its mass adoption quite difficult. Based on that, a novel framework for contact tracing using blockchain as its infrastructure is presented. By integrating blockchain with contact tracing applications, user privacy can be guaranteed, while also providing people and government bodies with a complete public view of all confirmed cases. Moreover, we also investigate how public locations can aid in the contact tracing process by measuring the risk of exposure to COVID-19 to the general public and advertising it in a blockchain. By doing so, these locations can effectively report potential infection risks, while also guaranteeing privacy and trustworthiness in the information. Lastly, numerical results are shown in different scenarios and conclusions are drawn.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Imran, Professor Muhammad and Zhang, Professor Lei and Valente Klaine, Mr Paulo and Sun, Dr Yao and Xu, Mr Hao
• Authors: Valente Klaine, P., Zhang, L., Zhou, B., Sun, Y., Xu, H., and Imran, M.
• College/School: College of Science and Engineering > School of Engineering > Systems Power and Energy
• Journal Name: IEEE Internet of Things Magazine
• Publisher: IEEE
• ISSN: 2576-3180
• ISSN (Online): 2576-3199
• Published Online: 27 October 2020
• Copyright Holders: Copyright © 2020 IEEE
• First Published: First published in IEEE Internet of Things Magazine 3(3): 58-63
• Publisher Policy: Reproduced in accordance with the publisher copyright policy