Enabling Collusion-Resistant Hierarchical Attribute-Based Multi-Keyword Search for Personal Health Records Systems in Cloud

Abstract

The proliferation of cloud-based healthcare services has created a growing demand for secure and fine-grained sharing of Personal Health Records (PHRs). To support layered access control, Hierarchical Attribute-Based Keyword Search (HABKS) schemes have been developed. However, existing designs suffer from inherent collusion vulnerabilities that is users with access to different subtrees can jointly recover higher-level secrets, breaking access boundaries. To address this problem, we propose a collusion-resistant hierarchical multi-keyword searchable encryption scheme for privacy-preserving PHR sharing. Different from the previous HABKS, our scheme effectively prevents the propagation dependence of data encryption keys at nodes and user collusion attacks. This benefits from the root node key decoupling mechanism we designed, which enables each policy subtree to generate keys with embedded randomness. Additionally, we design an identity-bound trapdoor and a dual verification mechanism that tightly bind user attributes and keyword tokens, ensuring verifiable and fine-grained access control. Our scheme supports expressive multi-keyword queries with constant-size trapdoors, and offloads most pairing operations to the cloud, requiring only one pairing locally. Security proofs and experimental results confirm that our scheme achieves strong collusion resistance, efficient keyword retrieval, and practical suitability for secure hierarchical PHR systems.