Anonymity Preserving IoT-Based COVID-19 and Other Infectious Disease Contact Tracing Model
Autor: | Lalit Garg, Emeka Chukwu, Chinmay Chakraborty, Gaurav Garg, Nidal Nasser |
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Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
blockchain
IoT General Computer Science Computer science Biomedical Engineering digital health 02 engineering and technology Computer security computer.software_genre privacy Contact tracing 0202 electrical engineering electronic engineering information engineering General Materials Science Isolation (database systems) RFID Infectious Disease Contact Tracing General Engineering COVID-19 020206 networking & telecommunications Object (computer science) Digital health TK1-9971 Communications technology 020201 artificial intelligence & image processing Privacy law telemedicine Electrical engineering. Electronics. Nuclear engineering hospitals computer Anonymity |
Zdroj: | IEEE Access, Vol 8, Pp 159402-159414 (2020) Ieee Access IEEE Access |
ISSN: | 2169-3536 |
Popis: | 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. |
Databáze: | OpenAIRE |
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