Publication Type
Journal Article
Version
acceptedVersion
Publication Date
11-2016
Abstract
Online personal health record (PHR) is more inclined to shift data storage and search operations to cloud server so as to enjoy the elastic resources and lessen computational burden in cloud storage. As multiple patients' data is always stored in the cloud server simultaneously, it is a challenge to guarantee the confidentiality of PHR data and allow data users to search encrypted data in an efficient and privacy-preserving way. To this end, we design a secure cryptographic primitive called as attribute-based multi-keyword search over encrypted personal health records in multi-owner setting to support both fine-grained access control and multi-keyword search via Ciphertext-Policy Attribute-Based Encryption. Formal security analysis proves our scheme is selectively secure against chosen-keyword attack. As a further contribution, we conduct empirical experiments over real-world dataset to show its feasibility and practicality in a broad range of actual scenarios without incurring additional computational burden.
Keywords
Personal health record, Attribute-based encryption, Multi-keyword, Multi-owner, Chosen-keyword attack
Discipline
Databases and Information Systems | Information Security | Medicine and Health Sciences
Research Areas
Cybersecurity
Publication
Journal of Medical Systems
Volume
40
Issue
11
First Page
1
Last Page
12
ISSN
0148-5598
Identifier
10.1007/s10916-016-0617-z
Publisher
Springer Verlag (Germany)
Embargo Period
10-1-2017
Citation
MIAO, Yinbin; MA, Jianfeng; LIU, Ximeng; WEI, Fushan; LIU, Zhiquan; and WANG, Xu An.
m(2)-ABKS: Attribute-based multi-keyword search over encrypted personal health records in multi-owner setting. (2016). Journal of Medical Systems. 40, (11), 1-12.
Available at: https://ink.library.smu.edu.sg/sis_research/3272
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1007/s10916-016-0617-z
Included in
Databases and Information Systems Commons, Information Security Commons, Medicine and Health Sciences Commons