个人信息Personal Information
教授
博士生导师
硕士生导师
主要任职:软件学院、大连理工大学-立命馆大学国际信息与软件学院副院长
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:软件学院、国际信息与软件学院
学科:软件工程. 计算机应用技术
联系方式:guocheng@dlut.edu.cn
电子邮箱:guocheng@dlut.edu.cn
Fine-grained Database Field Search Using Attribute-Based Encryption for E-Healthcare Clouds
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论文类型:期刊论文
发表时间:2016-11-01
发表刊物:JOURNAL OF MEDICAL SYSTEMS
收录刊物:SCIE、PubMed、Scopus
卷号:40
期号:11
页面范围:235
ISSN号:0148-5598
关键字:Searchable encryption; Ciphertext-policy attribute-based encryption; Cloud computing; E-healthcare; Access control
摘要:An effectively designed e-healthcare system can significantly enhance the quality of access and experience of healthcare users, including facilitating medical and healthcare providers in ensuring a smooth delivery of services. Ensuring the security of patients' electronic health records (EHRs) in the e-healthcare system is an active research area. EHRs may be outsourced to a third-party, such as a community healthcare cloud service provider for storage due to cost-saving measures. Generally, encrypting the EHRs when they are stored in the system (i.e. data-at-rest) or prior to outsourcing the data is used to ensure data confidentiality. Searchable encryption (SE) scheme is a promising technique that can ensure the protection of private information without compromising on performance. In this paper, we propose a novel framework for controlling access to EHRs stored in semi-trusted cloud servers (e.g. a private cloud or a community cloud). To achieve fine-grained access control for EHRs, we leverage the ciphertext-policy attribute-based encryption (CP-ABE) technique to encrypt tables published by hospitals, including patients' EHRs, and the table is stored in the database with the primary key being the patient's unique identity. Our framework can enable different users with different privileges to search on different database fields. Differ from previous attempts to secure outsourcing of data, we emphasize the control of the searches of the fields within the database. We demonstrate the utility of the scheme by evaluating the scheme using datasets from the University of California, Irvine.