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User’s Privacy-preserving Technology For Precise Contact Tracing Of COVID-19

Posted on:2022-08-10Degree:MasterType:Thesis
Country:ChinaCandidate:Z J GuoFull Text:PDF
GTID:2544307169483374Subject:Computer Science and Technology
Abstract/Summary:PDF Full Text Request
At the heart of many government measures to contain the current COVID-19 infection and reduce potential subsequent impacts is the use of manual and smartphone-based contact tracing,which plays an important role in controlling the spread of epidemics.The technology aims to use smart phones to track personal location data,so that when a user is infected with a virus,it can quickly and accurately find high-risk people who have been in contact with them,and take corresponding measures to control the spread of the virus to a certain extent.However,in the application process,sensitive data from confirmed patients and unconfirmed users need to be used for analysis and judgment.Therefore,it is necessary to protect privacy while completing contact tracing.Contact tracing technology determines a user’s risk of infection by analyzing whether he or she has come into contact with a confirmed patient in the past.On this basis,the bayesian network model is introduced to more comprehensively consider the user’s age,whether there is a history of infection and other comprehensive factors.The trained model and the user’s private data are encrypted and uploaded to the remote server to complete the calculation and return to the user.The main contributions of this paper include two aspects:1)Design a privacy protection model for accurate contact tracking based on homomorphic encryption,calculate the infection risk of users by using the trajectory information provided by GPS positioning technology,and protect users’ privacy by using Paillier homomorphic encryption technology.The security of the scheme is proved by analysis,and the accuracy of the scheme is proved by comparison with the contact tracing scheme based on proximity detection.2)Design a security outsourcing scheme of The Bayesian network model,encrypt and upload the Bayesian network model which is used to predict the user’s infection risk based on multiple factors,encrypt and upload the user’s private information as well,complete the encryption calculation on the remote server,and feedback the result to the user.The correctness of the outsourcing scheme is proved by formula reasoning,and the accuracy of the security outsourcing technology is verified by comparative experiments.
Keywords/Search Tags:Contact Tracing, Privacy Protection, Homomorphic Encryption
PDF Full Text Request
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