Privacy-preserving COVID-19 contact tracing solution based on blockchain

Liu, Momeng; Zhang, Zeyu; Chai, Wenqiang; Wang, Baocang

doi:10.1016/j.csi.2022.103643

Cited by 22 publications

(10 citation statements)

References 30 publications

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“…Sheinson et al [13] demonstrated how sequential Monte Carlo (SMC) methods can be used to track the COVID-19 pandemic in the US and estimate the impact of interventions on health outcomes and resource utilization. M Liu et al [14] offer an effective privacy preservation solution in automated tracing scenarios. BA Ojokoh et al [15] used a synthesis approach to provide an examine of current research efforts to predict the spread of COVID-19 on continents.…”

Section: Introductionmentioning

confidence: 99%

RETRACTED: SIR model for the spread of COVID-19: A case study

Salimipour

Mehraban

Ghafour

et al. 2023

Operations Research Perspectives

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Section: Introductionmentioning

confidence: 99%

RETRACTED: SIR model for the spread of COVID-19: A case study

Salimipour

Mehraban

Ghafour

et al. 2023

Operations Research Perspectives

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“…Accordingly, one of this study's key focuses is the negative effect of privacy on behavioral intentions. Several studies have focused on users' privacy on tracing apps, the measures to protect people's privacy ( 162 , 163 ), or individuals' concerns regarding privacy issues ( 10 ). This study reveals that when it comes to health issues, individuals are unconcerned with privacy risk.…”

Section: Contributions and Implicationsmentioning

confidence: 99%

Examining the Prediction of COVID-19 Contact-Tracing App Adoption Using an Integrated Model and Hybrid Approach Analysis

Alkhalifah

Bukar

2022

Front. Public Health

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COVID-19 contact-tracing applications (CTAs) offer enormous potential to mitigate the surge of positive coronavirus cases, thus helping stakeholders to monitor high-risk areas. The Kingdom of Saudi Arabia (KSA) is among the countries that have developed a CTA known as the Tawakkalna application, to manage the spread of COVID-19. Thus, this study aimed to examine and predict the factors affecting the adoption of Tawakkalna CTA. An integrated model which comprises the technology acceptance model (TAM), privacy calculus theory (PCT), and task-technology fit (TTF) model was hypothesized. The model is used to understand better behavioral intention toward using the Tawakkalna mobile CTA. This study performed structural equation modeling (SEM) analysis as well as artificial neural network (ANN) analysis to validate the model, using survey data from 309 users of CTAs in the Kingdom of Saudi Arabia. The findings revealed that perceived ease of use and usefulness has positively and significantly impacted the behavioral intention of Tawakkalna mobile CTA. Similarly, task features and mobility positively and significantly influence task-technology fit, and significantly affect the behavioral intention of the CTA. However, the privacy risk, social concerns, and perceived benefits of social interaction are not significant factors. The findings provide adequate knowledge of the relative impact of key predictors of the behavioral intention of the Tawakkalna contact-tracing app.

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“…Samuel et al 31 provide trust and authenticity to public media communication and deliver an accurate method to disseminate Covid‐19 information. The authors proposed a blockchain‐based contact tracing framework 32 . The zero‐knowledge proof is used to protect the privacy of close contacts.…”

Section: Literature Surveymentioning

confidence: 99%

“…The authors proposed a blockchain‐based contact tracing framework. 32 The zero‐knowledge proof is used to protect the privacy of close contacts. It also uses an aggregate signature scheme to improve signature verification efficiency.…”

Section: Literature Surveymentioning

confidence: 99%

CovidBChain: Framework for access‐control, authentication, and integrity of Covid‐19 data

Pawar

Sachdeva

2022

Concurrency and Computation

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In the Covid-19 pandemic, information about the medical equipment such as personal protective equipment, ventilators, testing kits, oxygen cylinders, ICU beds, and patient diagnostic status is a black box for the patients. This article proposes a blockchain-assisted Covid-19 big data chain (CovidBChain) framework to handle the Covid-19 data, which is of colossal size (volume), coming from different sources (variety) and generated at every time instance (velocity). CovidBChain is proposed to protect electronic health records and Covid-19 equipment's information from illegal modification. CovidBChain provides transparency, access control, and integrity to Covid-19 data. The status of critical equipment like ventilator, Covid-19 beds, oxygen cylinder, and ICU status each such operation is integrated into the CovidBChain as a transaction. A prototype has been simulated using Ganache, Metamask, InterPlanetary File System, and Reactjs. The comparative assessment using proof-of-work (PoW) and proof-of-authority (PoA) deduces that the upload and retrieval time in PoA is less than PoW, while the transaction cost is more in PoW. The overhead of message exchange communication is reduced by a factor of 4.3× in PoA as compared to the PoW approach. CovidBChain has been tested on the Ethereum official test network Ropsten for PoW and Goerli for PoA.

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Privacy-preserving COVID-19 contact tracing solution based on blockchain

Cited by 22 publications

References 30 publications

RETRACTED: SIR model for the spread of COVID-19: A case study

RETRACTED: SIR model for the spread of COVID-19: A case study

Examining the Prediction of COVID-19 Contact-Tracing App Adoption Using an Integrated Model and Hybrid Approach Analysis

CovidBChain: Framework for access‐control, authentication, and integrity of Covid‐19 data

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