Cao, T.; Pan, Y.; Chen, H.; Zheng, J.; Hu, T. PPChain: A Blockchain for Pandemic Prevention and Control Assisted by Federated Learning. Bioengineering2023, 10, 965.
Cao, T.; Pan, Y.; Chen, H.; Zheng, J.; Hu, T. PPChain: A Blockchain for Pandemic Prevention and Control Assisted by Federated Learning. Bioengineering 2023, 10, 965.
Cao, T.; Pan, Y.; Chen, H.; Zheng, J.; Hu, T. PPChain: A Blockchain for Pandemic Prevention and Control Assisted by Federated Learning. Bioengineering2023, 10, 965.
Cao, T.; Pan, Y.; Chen, H.; Zheng, J.; Hu, T. PPChain: A Blockchain for Pandemic Prevention and Control Assisted by Federated Learning. Bioengineering 2023, 10, 965.
Abstract
A pandemic can have a huge impact on normal human life and the economy, taking COVID-19 as an example. While the population flow between countries and regions is the main factor affecting the change of a pandemic, exactly as the airline network. Therefore, realizing the overall control of airports is an effective way to control a pandemic. However, restricted to the differences in prevention and control policies in different areas and privacy issues, the patients’ personal data of the medical center cannot be effectively combined with the passengers’ personal data. This prevents more precise airport control decisions from being made. To the end, this paper designs a novel data sharing framework (i.e., PPChain) based on blockchain and federated learning. The experiment shows that the relationship between the epidemic and aircraft transport can be effectively explored by PPChain, without sharing raw data. This approach does not require centralized trust and improves the security of the shareing process.The scheme can help formulate more scientific and rational prevention and control policies on airports’ control. And it can use aerial data to predict pandemics more accurately.
Keywords
blockchain; federated learning; pandemic prevention and control; privacy-preserving
Subject
Public Health and Healthcare, Public Health and Health Services
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.