A Verifiable Privacy-Preserving Data Aggregation Scheme with Illegal Data Detection for Infectious Disease Surveillance Systems

With various infectious diseases spreading globally, Infectious Disease Surveillance (IDS) plays a crucial role in stopping the spread of infectious diseases. Data aggregation techniques are commonly used to avoid user privacy leakage caused by infectious disease surveillance data transmission. However, none of the currently proposed data aggregation schemes simultaneously consider security issues such as untrustworthy aggregation nodes, illegal signature localization and identity anonymization. To address the above issues, this scheme proposes verifiable data security communication scheme with illegal data detection for infectious disease surveillance systems (VDSCS-IDS). Specifically, we use homomorphic encryption and signature techniques with batch verification to ensure the confidentiality and integrity of data. Then, VDSCS-IDS utilizes a pseudonym mechanism to prevent user identity disclosure. In addition, we can efficiently perform illegal signature localization, which improves the robustness of secure message interactions. We use a commitment mechanism to solve the problem of untrustworthy third-party aggregation nodes. Particularly noteworthy is the scheme's ability to perform diverse data statistics. Security analysis shows that the scheme achieves the desired security performance. Detailed performance analysis proves that the scheme is feasible with excellent computational and communication performance and can be applied to IDS securely and efficiently.