Efficient Privacy-Preserving Conjunctive Searchable Encryption for Cloud-IoT Healthcare Systems
Jiadi Ma, Tianqi Peng, Bei Gong, Muhammad Mohsin Waqas, Hisham Alasmary, Sheng Chen · ACM Transactions on Privacy and Security · 2025
In cloud-Internet of Things (IoT) healthcare systems, private medical data leakage is a serious concern as the cloud server is not fully trusted. Dynamic searchable symmetric encryption (DSSE), with necessary forward and backward privacy security properties, enables doctors to retrieve ciphertexts while guaranteeing data privacy. However, existing forward and backward private DSSE schemes are not well-suited for cloud-IoT healthcare systems with attribute-value type databases. To this end, we propose an efficient privacy-preserving conjunctive searchable encryption scheme for cloud-IoT healthcare systems, called PC-SE. It is the first conjunctive DSSE scheme designed for attribute-value type databases. Specifically, we design flexible search capabilities for PC-SE to address users’ various search requirements. It can not only achieve precise conjunctive search based on keywords but also realize broad attribute search. Moreover, our scheme achieves fine-grained search for attribute values while maintaining forward and Type-I - backward privacy. This approach reduces the communication burden and minimizes the risk of privacy exposure. To ensure that users with different authorities can only access the corresponding attribute values, we introduce an attribute access control mechanism in PC-SE. Finally, security analysis and experimental results demonstrate that PC-SE is secure and effective.