Fog-Assisted Composite Attribute-Based Encryption for Secure Personal Health Data Sharing

The exponential growth of wearable medical devices (WMDs) and the increasing demand for real-time health data sharing necessitate secure and fine-grained access control mechanisms. However, existing ciphertext-policy attribute-based encryption (CP-ABE) schemes suffer from computational and storage overheads that grow linearly with policy complexity. To address this challenge, we propose fog-assisted composite attribute-based encryption (FA-CABE), a novel scheme that integrates composite attributes with fog computing to enhance efficiency. FA-CABE leverages the subset sum problem (SSP) to map conjunctive policy clauses to composite attributes, substantially reducing both encryption and decryption overhead. A dualfog-node architecture offloads cryptographic computations from WMDs, enabling lightweight local processing. Rigorous security analysis under the Decisional Bilinear Diffie-Hellman (DBDH) assumption demonstrates that FA-CABE achieves replayable chosen ciphertext attack (RCCA) security. Experimental results show that FA-CABE achieves encryption speeds that are 22.13×–145.02× faster and decryption speeds that are 6.71×–161.83× faster than existing schemes, while requiring only a constant number of operations for decryption. Additionally, experimental validation on the Raspberry Pi 4B shows that the energy consumption is as low as 0.72 W per core, with data processing speed reaching 23.38 MB/s.