scholarly journals An Effective Data Access Method for Public Cloud Data Storage

These days attribute-based encryption has been gotten as a promising strategy to give versatile and secure data to oversee the conveyed storage in the cloud registering environment. In the attribute-based encryption plan, the single property pro should execute the customer legitimacy check and mystery key flow, and thusly, its outcomes. Customers may be stuck in the believing that at a stretch get their mystery keys and choose to get the required data from Cloud. So as to maintain a strategic distance from the single-point execution bottleneck, we are proposing multi-master access control plan which will assess the issue such way that it gives increasingly successful access control on cloud data to the clients.

2021 ◽  
Vol 13 (11) ◽  
pp. 279
Author(s):  
Siti Dhalila Mohd Satar ◽  
Masnida Hussin ◽  
Zurina Mohd Hanapi ◽  
Mohamad Afendee Mohamed

Managing and controlling access to the tremendous data in Cloud storage is very challenging. Due to various entities engaged in the Cloud environment, there is a high possibility of data tampering. Cloud encryption is being employed to control data access while securing Cloud data. The encrypted data are sent to Cloud storage with an access policy defined by the data owner. Only authorized users can decrypt the encrypted data. However, the access policy of the encrypted data is in readable form, which results in privacy leakage. To address this issue, we proposed a reinforcement hiding in access policy over Cloud storage by enhancing the Ciphertext Policy Attribute-based Encryption (CP-ABE) algorithm. Besides the encryption process, the reinforced CP-ABE used logical connective operations to hide the attribute value of data in the access policy. These attributes were converted into scrambled data along with a ciphertext form that provides a better unreadability feature. It means that a two-level concealed tactic is employed to secure data from any unauthorized access during a data transaction. Experimental results revealed that our reinforced CP-ABE had a low computational overhead and consumed low storage costs. Furthermore, a case study on security analysis shows that our approach is secure against a passive attack such as traffic analysis.


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