Lightweight-blockchain based privacy-preserving data aggregation for epidemic disease surveillance

Abstract

As the COVID-19 pandemic is raging worldwide, epidemic surveillance helps prevent the spread of the epidemic. Protecting the privacy of patients and data providers in the monitoring system can relieve them of their concerns about the leakage of private information, thereby improving the epidemic data collection capabilities of the system. In this article, we propose a lightweight-blockchain based privacy-preserving data aggregation scheme (LBPDA) for epidemic disease surveillance, which can aggregate data without relying on a trusted third party. Especially, to protect data privacy in the data aggregation process, the case count data is aggregated based on the Paillier cryptosystem's homomorphism. Besides, to reduce the time and storage overhead, we improved the adopted Hyperledger Fabric, thus lightening the data aggregation process. Finally, we simulated the proposed scheme and analyzed its security and performance to verify its feasibility and effectiveness. The results showed that the proposed scheme could meet the government department's requirements to aggregate patient case count data for epidemic disease surveillance while protecting the privacy of patients and data providers. Moreover, we also proved that the lightweight of blockchain is effective by comparison.