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Cloud-based electronic health record system supporting fuzzy keyword search
- Source :
- Soft Computing. 20:3243-3255
- Publication Year :
- 2015
- Publisher :
- Springer Science and Business Media LLC, 2015.
-
Abstract
- As cloud computing becomes prevalent, electronic health record (EHR) system has appeared in the form of patient centric, in which more and more sensitive information from patients is being uploaded into the cloud. To protect patients' privacy, sensitive EHR information has to be encrypted before outsourcing. However, this makes effective data utilization, such as fuzzy keyword search and data sharing, a very challenging problem. In this paper, aiming at allowing for securely storing, sharing and effectively utilizing the EHR, a new cloud-based EHR system is proposed. A binary tree is utilized to store the encrypted records in the proposed scheme, and an attribute-based encryption scheme is applied to encrypt the secret keys. The proposed system is very efficient because only symmetric encryption is introduced to encrypt the records. To support effectively retrieve patients' records, an efficient fuzzy keyword search over encrypted data is proposed without reliance on heavy cryptographic operations, which greatly enhances system usability by returning the matching files. With rigorous security analysis, we show that the proposed scheme is secure, while it realized privacy-preserving data sharing and fuzzy keyword search. Extensive experimental results illustrate the efficiency of the proposed solution.
- Subjects :
- Information privacy
Database
business.industry
Computer science
020206 networking & telecommunications
Cloud computing
Cryptography
02 engineering and technology
Encryption
computer.software_genre
Theoretical Computer Science
Data sharing
Upload
Information sensitivity
Symmetric-key algorithm
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Geometry and Topology
Data mining
business
computer
Software
Subjects
Details
- ISSN :
- 14337479 and 14327643
- Volume :
- 20
- Database :
- OpenAIRE
- Journal :
- Soft Computing
- Accession number :
- edsair.doi...........25e3c46b57f8efc3657dd4a0a505c990
- Full Text :
- https://doi.org/10.1007/s00500-015-1699-0