ENHANCED RANDOM KEY GENERATION FORAUTHOIZED DEDUPLICATION FOR CLOUD ENVIRONMENT
Abstract
Deduplication is an approach that eliminates the repeated copies of data stored in the remote storage service, where users can upload and download their data anytime and anywhere. However, all the data are stored in the cloud storage that raises an issue regarding privacy and data confidentiality. To protect the confidentiality of sensitive data and support deduplication, the convergent encryption technique has been used to encrypt the data before outsourcing. In this paper a Content Defined Chunking(CDC) algorithm (Asymmetric Extremum (AE)) is used to enhance the performance of deduplication process in cloud. Based on the observation that the extreme value in an asymmetric local range is not likely to be replaced by a new extreme value in dealing with the boundaries-shifting problem. As a result, AE has higher chunking throughput, smaller chunk size variance than the existing CDC algorithms, and is able to find proper chunk boundaries in low-entropy strings. The experimental results based on real world datasets and remove the chunkingthroughput performance bottleneck of deduplication. The system throughput by more than 62%, while achieving comparable deduplication efficiency.
Author
A.Indhumathi
P.Abirami
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