Reconfigurable intelligent surface (RIS) has been viewed as a promising solution in constructing reconfigurable radio environment of the propagation channel and boosting ... View more Metadata

The sharing of electronic health records (EHRs) has great positive significance for research of disease and doctors' diagnosis. In recent years, cloud-based electronic medical record sharing scheme has brought a lot of conveniences, but the centralization of cloud exposes threats inevitably to data security and privacy preservation. Blockchain technology can be seen as a promising solution to address these problems on account of its unique propertis of decentration, anonymity, unforgeability and verifiability. In this paper, we propose a blockchain based secure and privacy-preserving EHR sharing protocol. Data requester can search desired keyword from data provider to find relevant EHRs on the EHR consortium blockchain and get the re-encryption ciphertext from cloud server after getting the data owner's authorization. The scheme mainly uses searchable encryption and conditional proxy re-encryption to realize data security, privacy preservation, and access control. Furthermore, proof of authorization is designed as the consensus mechanism for consortium blockchain to guarantee system's availability. Security analysis demonstrates that the proposed protocol can achieve security goals. Besides, we emulate the cryptographic primitives and implement the proposed scheme on Ethereum platform. Performance evaluation shows that the proposed scheme has high computational efficiency.INDEX TERMS Electronic health records, data sharing, blockchain, data security, privacy preservation.

<abstract> <p>Since December 2019, an outbreak of a novel coronavirus pneumonia (WHO named COVID-19) swept across China. In Shanxi Province, the cumulative confirmed cases finally reached 133 since the first confirmed case appeared on January 22 2020, and most of which were imported cases from Hubei Province. Reasons for this ongoing surge in Shanxi province, both imported and autochthonous infected cases, are currently unclear and demand urgent investigation. In this paper, we developed a SEIQR difference-equation model of COVID-19 that took into account the transmission with discrete time imported cases, to perform assessment and risk analysis. Our findings suggest that if the lock-down date in Wuhan is earlier, the infectious cases are fewer. Moreover, we reveal the effects of city lock-down date on the final scale of cases: if the date is advanced two days, the cases may decrease one half (67, 95% CI: 66–68); if the date is delayed for two days, the cases may reach about 196 (95% CI: 193–199). Our investigation model could be potentially helpful to study the transmission of COVID-19, in other provinces of China except Hubei. Especially, the method may also be used in countries with the first confirmed case is imported.</p> </abstract>

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