Fine-Grained Ranked Multi-Keyword Search Over Hierarchical Data for IoT-Oriented Health System

With the rapid advance of the Internet of Things (IoT) and cloud computing technologies, the IoT-oriented health is expected to greatly improve the quality of healthcare service. However, data security and privacy concerns have become one of the biggest issues in smart health applications. As a potential and promising solution, attribute-based keyword search (ABKS) can provide fine-grained keyword search and access control over the encrypted data at the same time. Nevertheless, prior ABKS schemes cannot simultaneously support fine-grained, effective, and accurate data retrieval over hierarchical data. In this paper, to tackle these issues, we propose a fine-grained ranked multi-keyword search scheme over hierarchical data by leveraging ciphertext-policy hierarchical attribute-based encryption (CP-HABE) and ranked multi-keyword search (RMKS) technologies. Then, we prove that our proposed scheme is selectively secure through security analysis and we also show the practicability and feasibility of the proposed scheme by performance evaluation.