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

TL;DR

This paper introduces an access control-based privacy preservation model for secure healthcare data sharing in cloud environments, emphasizing mutual authentication, high security, and efficiency.

Contribution

It proposes a novel multi-entity digital system with specific phases for secure data sharing, enhancing robustness and outperforming existing methods in data rate.

Findings

Achieves a maximal genuine data rate of 0.91.

Provides high security and efficiency in healthcare data sharing.

System verified through multiple scenarios.

Abstract

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.