A Verifiable Epidemic Monitoring and Early Warning Scheme for Privacy Protection under Malicious Cloud Server Threat Model

XinMiao Ma

doi:10.63313/JCSFT.9054

Authors

XinMiao Ma Qingdao University, Qingdao 266071, China Author

DOI:

https://doi.org/10.63313/JCSFT.9054

Keywords:

Cloud Computing, Epidemic diseases, Monitoring and early warning, Privacy-preserving, Verifiability of results

Abstract

The current epidemic monitoring and early warning systems usually directly upload raw disease data to the cloud server without verifying the aggregated results returned by the cloud server, which brings about the dual risks of data leakage and result tampering. To address these issues, this paper proposes a cloud-assisted privacy-preserving and verifiable epidemic monitoring and early warning scheme. This scheme encrypts the disease data by integrating technol-ogies such as convergent encryption(CE), hash-based indexing, and oblivious pseudorandom function (OPRF), and verifies the results returned by the cloud server to protect sensitive information during cloud storage and computing processes, while preventing malicious cloud servers from forging or tampering with data. The analysis shows that our solution can provide privacy protection and result verifiability, making it a feasible solution for epidemic monitoring and early warning.

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