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@article{145480,
        author = {P Nithin Kumar Reddy and J S Ananda Kumar},
        title = {A De-duplication Aware Similarity Recognition and Securing data in the Cloud},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {4},
        number = {10},
        pages = {789-792},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=145480},
        abstract = {Now a days cloud is used mainly for accessing and storing the data . We can access the data easily in the cloud. Mainly we are using cloud for storing our data which may be small or large data. If the same data is getting stored or accessing via cloud then there is lot of duplicated data. Data reduction has become increasingly important in storage systems due to the explosive growth of digital data in the world that has ushered in the big data era. One of the main challenges facing large-scale data reduction is how to maximally detect and eliminate redundancy at very low overheads. In this paper, we have a tendency to present a low-overhead De-duplication Aware likeness detection and Elimination theme that effectively exploits existing duplicate-adjacency info for extremely economical likeness detection in information de-duplication based mostly backup or archiving storage systems. the most plan behind DARE is to use a theme, call Duplicate-Adjacency based mostly likeness Detection (Dup Adj), by considering any 2 information chunks to be similar (i.e., candidates for delta compression) if their various adjacent information chunks at duplicate during a de-duplication system, then any enhance the resemblance detection potency by an improved super-feature approach.},
        keywords = {Data De-duplication, Delta compression, Cloud Storage System},
        month = {},
        }