Enhanced secure content Deduplication using effective hash Function and chunking logarithm

Abstract

Data Deduplication is one of trending data compression mechanism to remove duplicate copies of repeated data, and widely used in cloud storage server which reduces the unwanted utilized memory space and helps to identify the right owner of the content in the cloud. If there is only one copy of each data file stored in the cloud, the cloud has huge quantity of cloud users who own such data file. The existing method discusses a convergent encryption technique to solve the Deduplication problem. Convergent Encryption technique encrypts an input file with the hash value of the input file as an encryption key. The ciphertext is given to the server and the user retains the encryption key. Since convergent encryption is deterministic, identical files are always encrypted into identical ciphertext, regardless of who encrypts them. However, the method does not assure consistency, reliability and confidentiality in cloud. Similar or different cloud users store duplicated file in the cloud server, where cloud storage utilizes high volume of storage.To find a solution for the above problems, the work introduces Enhanced Secure Content Deduplication Identification and Prevention (ESCDIP) Algorithm to enhance the file-level and content-level Deduplication detection of encoded data with reliability in cloud environment. Every cloud user s files contain an independent master key for encryption using ESCDIP technique and outsource data into the cloud. It reduces the overheads that are associated with the interactive duplication detection and query processes. The proposed work identifies the unique data chunks to store in the cloud. When data owner is changed or new data owner is added to the group owner list, the encryption key is updated. The encrypted rekeying message acts as vital role to secure the content. newline