Anonymity Preserving IoT-Based COVID-19 and Other Infectious Disease Contact Tracing Model

Lalit Garg; Emeka Chukwu; Nidal Nasser; Chinmay Chakraborty; Gaurav Garg

doi:10.1109/ACCESS.2020.3020513

Anonymity Preserving IoT-Based COVID-19 and Other Infectious Disease Contact Tracing Model

IEEE Access. 2020 Aug 31:8:159402-159414. doi: 10.1109/ACCESS.2020.3020513. eCollection 2020.

Authors

Lalit Garg¹, Emeka Chukwu¹, Nidal Nasser², Chinmay Chakraborty³, Gaurav Garg⁴

Affiliations

¹ Department of Computer Information System (CIS)Faculty of Information Communication Technology (ICT), University of Malta 2080 Msida Malta.
² College of EngineeringAlfaisal University Riyadh 50927 Saudi Arabia.
³ Department of Electronics and Communication EngineeringBirla Institute of Technology at Mesra Ranchi 835215 India.
⁴ ABV-Indian Institute of Information Technology and Management Gwalior 474015 India.

Abstract

Automated digital contact tracing is effective and efficient, and one of the non-pharmaceutical complementary approaches to mitigate and manage epidemics like Coronavirus disease 2019 (COVID-19). Despite the advantages of digital contact tracing, it is not widely used in the western world, including the US and Europe, due to strict privacy regulations and patient rights. We categorized the current approaches for contact tracing, namely: mobile service-provider-application, mobile network operators' call detail, citizen-application, and IoT-based. Current measures for infection control and tracing do not include animals and moving objects like cars despite evidence that these moving objects can be infection carriers. In this article, we designed and presented a novel privacy anonymous IoT model. We presented an RFID proof-of-concept for this model. Our model leverages blockchain's trust-oriented decentralization for on-chain data logging and retrieval. Our model solution will allow moving objects to receive or send notifications when they are close to a flagged, probable, or confirmed diseased case, or flagged place or object. We implemented and presented three prototype blockchain smart contracts for our model. We then simulated contract deployments and execution of functions. We presented the cost differentials. Our simulation results show less than one-second deployment and call time for smart contracts, though, in real life, it can be up to 25 seconds on Ethereum public blockchain. Our simulation results also show that it costs an average of $1.95 to deploy our prototype smart contracts, and an average of $0.34 to call our functions. Our model will make it easy to identify clusters of infection contacts and help deliver a notification for mass isolation while preserving individual privacy. Furthermore, it can be used to understand better human connectivity, model similar other infection spread network, and develop public policies to control the spread of COVID-19 while preparing for future epidemics.

Keywords: COVID-19; Contact tracing; IoT; RFID; blockchain; digital health; hospitals; privacy; telemedicine.

This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.

Grants and funding

This work was supposed in part by Alfaisal University under Internal Research Grant C20220 and in part by the University of Malta’s Research Innovation & Development Trust (RIDT) under Research Grant E18LO77-01.