A searchable personal health records framework with fine-grained access control in cloud-fog computing

• Published in: PloS one 2018-11, Vol.13 (11), p.e0207543-e0207543
• Main Authors: Sun, Jin, Wang, Xiaojing, Wang, Shangping, Ren, Lili
• Format: Article
• Language: English
• Subjects: Access control; Applications programs; Cloud Computing; Computer and Information Sciences; Computer applications; Computer Security; Computer simulation; Data Mining; Earth Sciences; Electronic devices; Electronic Health Records; Electronic records; Encryption; Engineering and Technology; Fog; Humans; Information science; Information technology; Keywords; Latency; Medical records; Medicine and Health Sciences; Methods; Mobile Applications; Mobile computing; Mobile devices; Outsourcing; People and Places; Personal health; Physical Sciences; Privacy; Research and Analysis Methods; Searching; Servers; Technology; Wireless telephone software
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0207543

Fog computing can extend cloud computing to the edge of the network so as to reduce latency and network congestion. However, existing encryption schemes were rarely used in fog environment, resulting in high computational and storage overhead. Aiming at the demands of local information for terminal device and the shortcomings of cloud computing framework in supporting mobile applications, by taking the hospital scene as an example, a searchable personal health records framework with fine-grained access control in cloud-fog computing is proposed. The proposed framework combines the attribute-based encryption (ABE) technology and search encryption (SE) technology to implement keyword search function and fine-grained access control ability. When keyword index and trapdoor match are successful, the cloud server provider only returns relevant search results to the user, thus achieving a more accurate search. At the same time, the scheme is multi-authority, and the key leakage problem is solved by dividing the user secret key distribution task. Moreover, in the proposed scheme, we securely outsource part of the encryption and decryption operations to the fog node. It is effective both in local resources and in resource-constrained mobile devices. Based on the decisional q-parallel bilinear Diffie-Hellman exponent (q-DBDHE) assumption and decisional bilinear Diffie-Hellman (DBDH) assumption, our scheme is proven to be secure. Simulation experiments show that our scheme is efficient in the cloud-fog environment.