A Proposed Access Control-Based Privacy Preservation Model to Share
Healthcare Data in Cloud
- URL: http://arxiv.org/abs/2007.13850v1
- Date: Mon, 27 Jul 2020 20:32:51 GMT
- Title: A Proposed Access Control-Based Privacy Preservation Model to Share
Healthcare Data in Cloud
- Authors: Pankaj Khatiwada, Hari Bhusal, Ayan Chatterjee, Martin W. Gerdess
- Abstract summary: This paper presents the concept of an access control-based (AC) privacy preservation model for the mutual authentication of users and data owners.
The proposed model offers a high-security guarantee and high efficiency.
The proposed model outperforms other methods with a maximal genuine data rate of 0.91.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- 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.
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