Zechen Li

With the rapid development of the Internet of Things (IoT) and the increase in the number of various sensor devices, there is an increasingly urgent need for cross-domain sharing of massive data in scenarios, such as industrial control and smart healthcare, while the limitations of traditional encryption mechanisms in terms of interdomain segregation and dynamic privilege management have made proxy re-encryption (PRE) technology the core solution to address the secure flow of cross-domain data. Among them, attribute-based PRE is a promising approach. However, the existing schemes suffer from the inefficiency of interdomain transformation and the lack of dynamic privilege revocation mechanism which is crucial for data sharing systems. Therefore, in this article, we propose an efficient PRE scheme that supports dynamic privilege management and realizes secure cross-domain conversion from identity-based encryption (IBE) to attribute-based encryption (ABE). In this scheme, data is first encrypted by IBE mechanism and uploaded to a semi-trusted proxy server for storage, and the data owner can authorize the proxy server to convert the ciphertext to ABE ciphertext. Notably, our scheme achieves real-time updating of keys through an attribute revocation algorithm, which ensures that historical data cannot be decrypted after authorization changes and satisfies forward security. Meanwhile, the solution builds anti-collusion mechanism by jointly generating re-encryption key by the data owner and proxy server, which effectively protects against the joint attack of malicious users and proxy server, and prevents unauthorized users from decrypting the ciphertext. In addition, the computational burden is outsourced to the proxy server, and the user only needs to perform lightweight operations, which significantly reduces the computational overhead of the data owner in data sharing. Formal security proofs show that the scheme is indistinguishable under the chosen ciphertext attack (CCA) model (indistinguishability under CCA). Theoretical analysis and experimental results show that the structure is more efficient than previous schemes.

Remote surveillance is an effective method in restraining the spread of infectious diseases via monitoring crowds in affected areas. However, the monitoring targets in existing works are crowds, leading to high system cost, and most of them focus on finding close contacts, less considering the privacy protection and suspected treatment issues. To conquer above problems, this paper develops a new remote surveillance system for infectious diseases, which contains the following major contributions: (1) the monitoring targets are the ordinary contacts not all crowds, effectively decreasing the system cost; (2) establish the joint-control mechanism among contacts, health center, and the hospital to facilitate the prediagnosis and in-time treatment for suspected patients; (3) to avoid the privacy leakage of contacts, a double encryption strategy is designed to protect the location information, and a separating database-storage mechanism is used to improve the contact’s data security on the whole. Theoretical security analysis showed that the proposed system and privacy protection methods can effectively fight transmission attacks and avoid privacy leakage during data usage. Based on the created COVID-19 dataset, the simulation experiments were carried out to evaluate the effectiveness and feasibility of the proposed system, on the metrics of the accuracy of prediagnosis, encryption, and decryption time for health and location data. In summary, this work provides a promising way of low-cost remote surveillance system without privacy leakage to control the spreading of infectious disease.