R&D: Deep Learning Distributed Cloud Storage Systems for Secure Data Uploading With Chunk-Based De-Dupe

Solid State Technology has published an article written by Mrs. S.Ruba, and Dr. A.M.Kalpana.

Abstract: “Cloud computing was based on the infrastructural and conceptual basis with secure computing. Cloud-based services and service providers are being progressed which has resulted in cloud-based trending technology. In a cloud environment, the mechanism of privacy protection is based on the chunking process and analysis of deduplication with privacy protection in the distribution of data storage. If security is not robust and consistent, the flexibility and advantages of using deep learning have to offer credibility. In proposed system, the user uploads new data in cloud computing. There are two processes applied for security analysis: Deduplication and Chunking process. The user request keyword which is compared with the spare index of hash term and this term was stored by the chunking process. The proposed algorithm of Reliability-based Neural Collaborative Filtering (RNCF) is used for chunking the cloud data content in three ways such as granularity, point of application, and time of application. RCNF algorithm Spare index term was compared with deduplication analysis. If the chunk data mismatched with user request, then the request will be responded to the user. Suppose if the chunk data matched with the user keyword then the proposed algorithm of Deep learning (DL) techniques are applied for security purposes. The Distributed Secure Cloud Data Chunk (DSCDC) algorithm is used for the security process for authorizing the user, if thread analyzed then blocks the user. Deduplication is analyzed and security level is checked through the proposed DL algorithm. Experimental results shown on the real-world dataset of cloud data shows its efficiency, security, and effectiveness.“