Cloud computing based deduplication using high-performance grade byte check and fuzzy search technique

Abstract

Background: Data redundancy (DR) and data privacy (DP) is a critical issue that increases storage and security problems in cloud environments. Data de-duplication (DD) is one of the efficient backup storage techniques to reduce DR. The main problem with using cloud computing (CC) is more storage, the cost of deployment and maintenance. Objective: To minimize this problem, High-performance Grade Byte Check and Fuzzy search Techniques (HP-GBC-FST) based DD is proposed in this paper. Methods: The HP-GBC-FST is based on the pre-process of data by comparing their first byte and categorizing the byte based on the first byte. After DD, encryption has been processed on data to improve the data security in the cloud environment and then encrypted data is stored in the cloud. This HP-GBC-FST recognizes DR at the block level, reducing the redundancy of data more effectively. Then, HP-GBC-FST is created to detect and eliminate duplicates, improve security and storage efficiency (SE), reduce DD time and computation cost (CPC) in the DD verification and auditing phase. Result: The experiment has been conducted in an Intel I5 system and 500GB, 1Tb memory space and implemented in the Java programming environment. The results of the experiment reveal that the HP-GBC-FST improved the DD ratio and security by 3.7 and 97%, respectively, and reduced the DD time and CPC by 87% and 84.4%, respectively, over the existing technique. Conclusion: It concluded that the HP-GBC-FST has greater improvement over DD data in the cloud. Finally, the performance analysis of the HP-GBC-FST achieves higher storage, both privacy and security attributes, and incurs minimal CPC, DD time compared with the state he art research.