Security is important in cloud data storage while using the cloud servicesprovided by the service provider in the cloud. Most of the research works have beendesigned for a secure cloud data storage. However, cloud users still have securityissues with their outsourced data. In order to overcome such limitations, a DynamicBloom Filter Hashing based Cloud Data Storage (DBFH-CDS) Technique isproposed. The main goal of DBFH-CDS Technique is to improve confidentiality andsecurity of data storage in a cloud environment. The proposed Technique isimplemented using data fragmentation model and Bloom filter. The DBFH-CDSTechnique uses data fragmentation model for fragmenting the large cloud datasets.After that, Bloom Filter is employed in DBFH-CDS Technique for storing thefragmented sensitive data along with higher security. The DBFH-CDS Techniqueensures high data confidentiality and security for cloud data storage with the help ofBloom Filter. The performance of proposed DBFH-CDS Technique is measured interms of Execution time and Data retrieval efficiency. The experimental results showthat the DBFH-CDS Technique is able to improve the cloud data storage securitywith minimum space complexity as compared to state-of-the-art-works.
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