A Proposed Access Control-Based Privacy Preservation Model to Share Healthcare Data in Cloud

被引:5
作者
Khatiwada, Pankaj [1 ]
Bhusal, Hari [1 ]
Chatterjee, Ayan [1 ]
Gerdes, Martin W. [1 ]
机构
[1] Univ Agder, Fac Engn & Sci, Grimstad, Norway
来源
2020 16TH INTERNATIONAL CONFERENCE ON WIRELESS AND MOBILE COMPUTING, NETWORKING AND COMMUNICATIONS (WIMOB) | 2020年
关键词
Access control; Key generation center; privacy preservation; cloud model; data sharing;
D O I
10.1109/wimob50308.2020.9253414
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Healthcare data in cloud computing facilitates the treatment of patients efficiently by sharing information about personal health data between the healthcare providers for medical consultation. Furthermore, retaining the confidentiality of data and patients' identity is a another challenging task. This paper presents the concept of an access control-based (AC) privacy preservation model for the mutual authentication of users and data owners in the proposed digital system. The proposed model offers a high-security guarantee and high efficiency. The proposed digital system consists of four different entities, user, data owner, cloud server, and key generation center (KGC). This approach makes the system more robust and highly secure, which has been verified with multiple scenarios. Besides, the proposed model consisted of the setup phase, key generation phase, encryption phase, validation phase, access control phase, and data sharing phase. The setup phases are run by the data owner, which takes input as a security parameter and generates the system master key and security parameter. Then, in the key generation phase, the private key is generated by KGC and is stored in the cloud server. After that, the generated private key is encrypted. Then, the session key is generated by KGC and granted to the user and cloud server for storing, and then, the results are verified in the validation phase using validation messages. Finally, the data is shared with the user and decrypted at the user-end. The proposed model outperforms other methods with a maximal genuine data rate of 0.91.
引用
收藏
页数:8
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