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In cloud computing environment the owners store their data from their local system to the cloud storage. More data owners store large data into the cloud storage. New security challenges are there, when owner store their data in the cloud storage ie the data owner may be bothered that the data could be misplaced or modify in the cloud storage. This is because in any infrastructure the data loss may happen due to hardware and software failure and human error. Sometimes, the cloud service providers itself may remove the data which has not been used or not often used to enlarge the storage space. We recommend a new scheme to validate the availability and integrity of the outsourced files which uses the checksum value and is implemented using Hadoop. The proposed method requires less computation and storage.

Cloud computing facilitates extremely scalable serv ices that can be consumed over internet. An importa nt aspect of the cloud services is that user data are stored remotely in unknown machines in which users do not posses or manage. Since the data’s are stored remot ely, we have to keep in mind that sensitive cloud d ata have to be encrypted before they are outsourced to the commercial public cloud, which makes efficient data utilization service. Searchable encryption file ret rieval technique allows users to securely search ov er encrypted data through search word. Ranking the fil es based on relevance scores greatly enhances syste m usability by making it possible relevance ranking i nstead of sending unwanted results and further ensu res the file retrieval accuracy. In this study, we are developing an automated system for both named and unnamed documents based on the clustering algorithms. We implement the ranking and searching algorithm to retrieve top k files. We also provides the mapping and encryption algorithm to protect the information . The resulting design is able to provide efficient ranki ng which will reduce the search time drastically an d reduce the communication overhead. The mapping and encryption algorithms protect document against an outside attackers and prevent an untrusted cloud data provi der from learning data.

A storage system in cloud is well thought-out as a very big scale storage system that has independent storage servers. The service that cloud storage provides is, that can store user's data from remote through network and other authenticated users can access the data easily. Hadoop distributed file system is used to store large files consistently and to retrieve those files at very high bandwidth to user applications. Hadoop splits the files into large blocks and distributes them amongst the nodes in the cluster. When we retrieve data from the cloud, it is very important that the computation and communication overhead should be reduced. To reduce the communication overhead the server should send only the top-n files based on the keyword when the user asks for the data files. Since the owner need not maintain the copy of the files, it is all the more necessary to make check on the files available and also check the originality of the files stored in the server periodically. In HDFS the computation is done in parallel so that the execution time is drastically reduced. In the proposed system for retrieving top-n files we use Hadoop Distributed File System, so that the search time and the communication overhead is greatly reduced.

Cloud computing provide the owner to store their data into the cloud servers and data consumers can access the data from cloud by on demand. By outsourcing the data, the owners can no need to maintain the data locally. Due to this, the owner requires the auditing service to verify the correctness of the data stored in the cloud servers. To reduce the communication cost the server should return only the relevance files while the user request for the data files. Sharing relevance data and checking the integrity of the outsourced data is still a challenging issue. Ranked search greatly enhances system usability by returning the matching files in a ranked order regarding to certain relevance criteria .Our proposed system is developed based on the fragment structure , hash index hierarchy and top n query algorithm to retrieve the n number of best matched results for the given query. In addition we provide a load balancing scheme to process the jobs submitted to the server. Our experimental results prove that the proposed system is highly efficient and secured.