Data growth rates will proceed to
build faster in the coming years. Cloud computing provides a new way of service
provision by arranging various resources over internet. One of the important
cloud service amongst the existing services is storage of data. Data saved
might hold multiple copies of the same data. Data deduplication is one of the vital
techniques, which compress the data by removing the duplicate copies of the
same data to minimize the storage space. In order to provide the data
protection which is to be stored on cloud, data are need be stored in the
encrypted form. In proposed scheme the main purpose of this is to ensure that
only one instance of data is stored, lower the amount of storage space, and
optimize storage capacity. Here we design a effective approach which
effectively reduces encryption overhead using compression and encryption




        Cloud computing is an IT that enables
access to shared pools of configurable system resources and higher-level services that can be
rapidly provisioned with minimal
management effort, often over the Internet. Cloud
computing services all work a little differently. Cloud computing relies on sharing of resources to
achieve coherence and economy of scale, similar to a utility. But
many provide a friendly, browser-based dashboard that makes it easier for IT
professionals and developers to order resources and manage their accounts. Some
cloud computing services are also designed to work with APIs and CLI, giving
developers multiple options. Some of the things we can do with the cloud are
creating new app and service, storing, back up and recover data, stream audio
and video. Cloud provides three types of services: IASS, PAAS, SAAS and three
cloud deployments: public, private and hybrid.

The idea of data
deduplication was proposed to minimize the storage space. It is also called as
intelligent compression or single instance storage. In this paper we design and
develop a new approach that effectively deduplicates redundant data in document
by using the concept of object level component resulting to less data chunking,
uses fewer indexes and reduced need for tape backup. This technique focuses on
improving utilization and also can be applied to network data transfer to
reduce number of bytes that must be sent. Data deduplication can operate at
file level, block level and even at bit level. In file-level data
deduplication, if any two files are exactly alike then only one copy of file
need to be stored then subsequent iteration will have a pointer to files. The
change in the single bit will need to store entire copy of different file. In
block-level and bit-level data deduplication it looks within a file, if file is
updated then it saves only the changed blocks between the two files. However
file-level may require less processing power due to smaller index and reduce
the number of comparison but in block- level may take more processing power and
use much larger index to track the individual block.