Saltar al contenido principal

ETHNOS_APP

Inicio • Búsqueda • Revistas • Lista 0

Blockchain-Driven Privacy-Preserving Contact-Tracing Framework in Pandemics

Datos Bibliográficos

ID22106918
AutoresXiao Li (0000-0002-6762-2475, The University of Texas at Dallas), Weili Wu (0000-0001-8747-6340, The University of Texas at Dallas), Tiantian Chen (0000-0003-3513-6170, The University of Texas at Dallas)
Año2024
Volumen11
Número3
Páginas4279-4289
Fecha de publicación2024-06-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaIEEE Transactions on Computational Social Systems (JOURNAL)
Identificadores de la revistaISSN: 2329-924X • E-ISSN: 2373-7476
EditorialInstitute of Electrical and Electronics Engineers (IEEE) (PUBLISHER)
DOI10.1109/tcss.2024.3351191
OpenAlexW4391235428
IdiomaEN
Referencias citadas34

Blockchain technology, recognized for its decentralized and privacy-preserving capabilities, holds potential for enhancing privacy in contact tracing applications. Existing blockchain-based contact tracing frameworks often overlook one or more critical design details, such as the blockchain data structure, a decentralized and lightweight consensus mechanism with integrated tracing data verification, and an incentive mechanism to encourage voluntary participation in bearing blockchain costs. Moreover, the absence of framework simulations raises questions about the efficacy of these existing models. To solve above issues, this article introduces a fully third-party independent blockchain-driven contact tracing (BDCT) framework, detailed in its design. The BDCT framework features an Rivest-Shamir-Adleman (RSA) encryption-based transaction verification method (RSA-TVM), achieving over 96% accuracy in contact case recording, even with a 60% probability of individuals failing to verify contact information. Furthermore, we propose a lightweight reputation corrected delegated proof of stake (RC-DPoS) consensus mechanism, coupled with an incentive model, to ensure timely reporting of contact cases while maintaining blockchain decentralization. Additionally, a novel simulation environment for contact tracing is developed, accounting for three distinct contact scenarios with varied population density. Our results and discussions validate the effectiveness, robustness of the RSA-TVM and RC-DPoS, and the low storage demand of the BDCT framework

Blockchain · Computer security · Contact tracing · Cryptography · Database · Database transaction · Distributed computing · Incentive · Tracing · Blockchain Technology Applications and Security · Computer Science · COVID-19 Digital Contact Tracing · Privacy-Preserving Technologies in Data

  • Cloud/Edge Computing Resource Allocation and Pricing for Mobile Blockchain

    Open Access•Yuqi Fan, Lunfei Wang et al.•IEEE Transactions on Computational…•2021

  • Applications of Lorenz Curves in Economic Analysis

    Nanak Kakwani, N C Kakwani•Econometrica•1977

  • A Formula for the Gini Coefficient

    Robert Dorfman•The Review of Economics and…•1979

  • Covid-19 and Health Code

    Open Access•Fan Liang•Social Media + Society•2020

Velocidad de citaciónhistorical
Altamente citadoNo
Ethnos_APP • Proyecto Open Source • Licencia MIT • Frontend v2.0.0 • Privacidad y Cookies • Documentación de la API: api.ethnos.app/docs • Código de la API: GitHub • DOI: 10.5281/zenodo.17049435 • Código del Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae